diversity and inclusivity in video game advertisements

DIVERSITY AND INCLUSIVITY IN VIDEO GAME ADVERTISEMENTS: AN EXPLORATION OF VIDEO GAME CONSOLE COMMERCIALS

FROM 2003 TO 2017

Alexander Michael Vollbach

A Thesis

Submitted to the Graduate College of Bowling Green State University in partial fulfillment of

the requirements for the degree of

MASTER OF ARTS

May 2018

Committee:

Lisa Hanasono, Committee Co-Chair

Lara Lengel, Committee Co-Chair

Joshua Atkinson

© 2018

Alexander Michael Vollbach

All Rights Reserved

iii

ABSTRACT

Lisa Hanasono, Committee Co-Chair

Lara Lengel, Committee Co-Chair

Drawing from cultivation theory, this project’s main goals were to examine television

advertisements for video game consoles produced by Microsoft, Nintendo, and Sony, and to

identify variations and trends in their racial, gender, and age representations between the years of

2003 and 2017. A quantitative content analysis was conducted on a representative sample of 70

commercials, where characters were coded separately for perceived gender, racial, and age

identity. A series of chi-square tests revealed that while the advertisements tended to

underrepresent women, racial minorities, and non-adults, the inclusion of women increased

substantially between 2006 and 2011. Among many other observed trends, Nintendo tended to

include more non-adults and people of Asian and Pacific Islander descent than Sony and

Microsoft. The results of this exploration inform a discussion on the underrepresentation of

minority groups in advertising and its potential impact on certain groups in our society.

This thesis attempts to position itself as a step in the right direction in the research of

video games as a cultural phenomenon on par with that of television and film. The following

work sets itself apart from other articles and writings of the same kind primarily by scale and

breadth of scope. The observation of the industry over time provides better insights into growth

and trends than the snapshot studies of static years that are currently being published. Much of

the reason for the lack of studies such as this thesis likely has much to do with popular

predispositions staunchly embedded in our societal consciousness regarding the current state of

diversity and inclusivity in the video game industry. The results of this study will better inform

these relatively anecdotal assumptions. Further, it is important to note his thesis seems to find

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itself situated as the largest scale overview on representation in video game advertising to date,

poising itself as an important contributor to cultivation theory as it applies to the subject of

racial, age, and gender representation in video game console advertising.

Keywords: Video games; Advertising; Commercials; Diversity; Inclusivity; Cultivation Theory

v

ACKNOWLEDGMENTS

I would like to thank my parents, Pamela Vollbach and Michael Vollbach for believing in

me, for pushing me to succeed, and for all of the support, both emotional and financial, over the

past few years. I would also like to thank my girlfriend, Beth Hill, for her love and her patience

throughout the pursuit of my master's degree and always. Many thanks to all of my amazing and

supportive friends who have put up with my ups and downs over the past two years.

I would like to thank my co-worker and friend, Keith Crossman, for sharing with me his

intricate knowledge of Microsoft Word, and for being a level head off of which I could bounce

ideas. Of course, I would be remiss if I did not extend a very special thanks my second coder,

Gabriel Cruz, without whom none of this would be possible. Lastly, I would like to give thanks

to my wonderful advisors and committee members, Dr. Lara Lengel, Dr. Lisa Hanasono, and Dr.

Joshua Atkinson, for their wisdom, patience, and guidance throughout the writing and revision

processes of this thesis.

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TABLE OF CONTENTS

Page

CHAPTER I: INTRODUCTION .......................................................................................... 1

Justification and Background ..................................................................................... 2

CHAPTER II: REVIEW OF LITERATURE ....................................................................... 5

Representation and Gaming ....................................................................................... 5

Cultivation Theory ..................................................................................................... 11

Advertising ............................................................................................................ 16

CHAPTER III: RESEARCH QUESTIONS AND METHODOLOGY ............................... 19

Research Objectives .……………………………………………………………….. 20

Methodology…………………………………………………………………………. 20

Units of Analysis……………………………………………………............ 22

Codes………………………………………………….................................. 22

Video game company………………………………………………… 22

Year .................................................................................................... 22

Racial, gender, and age representation. ............................................. 23

Role .................................................................................................... 24

Collection Procedure .................................................................................................. 24

CHAPTER IV: DATA ANALYSIS AND RESULTS .......................................................... 26

Data Analysis ............................................................................................................ 26

Results ……................................................................................................................ 26

The Big Picture: Describing the Project’s Data ............................................. 27

Gender, Racial, and Age Representations by Company ................................ 28

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Gender representation ........................................................................ 28

Racial representation .......................................................................... 30

Age representation ............................................................................. 32

Gender, Racial, and Age Representations by Time Period ............................ 34




Gender, Racial, Age Representations by Company

Over Five Time Periods ................................................................................. 40




CHAPTER V: DISCUSSION ................................................................................................ 57

Key Findings and Implications .................................................................................. 58

Examining differences in racial, gender, and age representations

by video game company ................................................................................ 58

Examining differences in racial, gender, and age representation

over time ........................................................................................................ 60

Examining differences in racial, gender, and age representations

by company over time. ................................................................................... 62

CHAPTER VI: CONCLUSION ............................................................................................ 65

Limitations ............................................................................................................ 65

Future Research ......................................................................................................... 66

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REFERENCES……….. ........................................................................................................ 67

APPENDIX A: CODE BOOK USED TO ANALYZE THE DATA……………………… 73

APPENDIX B: CODING WORKSHEET………………………………………………… 77

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LIST OF FIGURES

Figure Page

1 Differences in Gender Representation by Company ................................................. 29

2 Differences in Racial Representation by Company ................................................... 31

3 Differences in Age Representation by Company ....................................................... 33

4 Differences in Gender Representation Over Time ..................................................... 35

5 Differences in Racial Representation Over Time ...................................................... 37

6 Differences in Representations of Age Over Time .................................................... 39

7 Differences in Representations of Gender by Microsoft Over Time ......................... 41

8 Differences in Representations of Gender by Nintendo Over Time .......................... 43

9 Differences in Representations of Gender by Sony Over Time ................................ 44

10 Differences in Racial Representation by Microsoft Over Time ................................ 46

11 Differences in Racial Representation by Nintendo Over Time ................................. 48

12 Differences in Racial Representations by Sony Over Time ...................................... 50

13 Differences in Representations of Age by Microsoft Over Time .............................. 52

14 Differences in Representations of Age by Nintendo Over Time ............................... 54

15 D ifferences in Representations of Age by Sony Over Time..................................... 56

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LIST OF TABLES

Table Page

1 Chi-Square Analysis of Differences in Gender Representation by Company ........... 29

2 Chi-Square Analysis of Differences in Racial Representation by Company ............ 31

3 Chi-Square Analysis of Differences in Age Representations by Company .............. 33

4 Chi-Square Analysis of Differences in Gender Representation Over Time .............. 35

5 Chi-Square Analysis of Differences in Racial Representations Over Time .............. 37

6 Chi-Square Analysis of Differences in Representations of Age Over Time ............. 39

7 Chi-Square Analysis of Differences in Representations of Gender by

Microsoft Over Time ................................................................................................. 41

8 Chi-Square Analysis of Differences in Representations of Gender by

Nintendo Over Time .................................................................................................. 42

9 Chi- Square Analysis of Differences in Representations of Gender by

Sony Over Time ......................................................................................................... 44

10 Chi-Square Analysis of Differences in Racial Representation by


11 Chi-Square Analysis of Differences in Racial Representation by


12 Chi- Square Analysis of Differences in Racial Representation by

Sony Over Time ......................................................................................................... 49

13 Chi-Square Analysis of Differences in Representations of Age by



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Sony Over Time ......................................................................................................... 55

RUNNING HEAD: DIVERSITY AND INCLUSIVITY IN GAMING 1

CHAPTER I: INTRODUCTION

In the past 15 years, video games have gone from a relatively popular hobby to a

dominant form of media, rivaling film and television. A study conducted by the Entertainment

Software Association (ESA) in 2015 was found that approximately 155 million people in the

U.S. play video games for three or more hours a day, which represented approximately 42% of

the country’s population (ESA, 2015). With such a considerable portion of the U.S. population

spending such a significant amount of their free time on video games, it is easy to understand

why more time should be spent studying the contents and the implications of these new media.

As other forms of media attempt to be more diverse and inclusive, so too have video

games. As video games have grown to be the juggernaut we see today, developers have

attempted to shift their target demographic away from young men (Fron, Fullerton, Morie &

Pearce, 2007), and towards the previously untapped market of women (Chess, Evans & Baines,

2016). This shift is noticed through advertising, particularly television commercials, which now

feature women more front and center in an active, engaged role with the product (Fron,

Fullerton, Morie & Pearce, 2007).

Other studies have looked at media representations in the video game industry, but none

have taken a step back to look at the greater picture. For example, Chess, Evans, and Baines’s

(2006) study looked at advertising in 2013 to discern the dominant media representation of the

average gamer. Williams, Martins, Consalvo, and Ivory (2009) examined the extent to which

video game representations reflected or deviated from the U.S. population’s demographics.

Another example of a similar study observed the phenomenon in which White males were the

only group to be considered truly as a gamer (Fron, Fullerton, Morie, & Pearce, 2007). There is a

gap in literature that may be filled through the study of racial, gender, and age representations in

DIVERSITY AND INCLUSIVITY IN GAMING 2

video games over time. In looking at top selling games at intervals of time, one may track the

trajectory of change in the representations in this popular media. In this chapter, the importance

of studying the continued movement towards diversity and accurate representation in video

games is defined, before drawing from relevant literature to propose this project’s research

questions.

Justification and Background

There appears to be a disconnect between video games and representation. According to

the authors of A Virtual Census, there is a clear problem with representation if one compared in-

game demographics to the actual population of the United States (Williams, Martins, Consalvo,

& Ivory, 2009). While certain groups were overrepresented (such as White and Asian

populations), other groups were severely underrepresented (such as Black and Hispanic

populations) (Williams, Martins, Consalvo, & Ivory, 2009). These findings are shocking for a

variety of reasons, most saliently being that these games do not come close to properly

representing those groups that engage with them. Williams, Consalvo, and Ivory (2009)

explained that Black and Hispanic populations are among those who have the highest percentage

of gamers to non-gamers, which presents a significant problem regarding impacts and social

responsibility.

As the authors so astutely point out, if a consumer of a media deemed culturally

influential by greater society does not see representations of their particular group very often (or

at all in the case of Native Americans), the impression that is given to these people is that they do

not matter (Williams, Martins, Consalvo, & Ivory, 2009). Though perhaps these effects are

unintentional, it is on the producers of content to address these issues and fix them, especially

when the content is consumed by a large, diverse population.


To frame this discussion of the criticality of building and maintaining proper

representation in another way, we can look to cultivation theory. As the theory states, a consumer

being barraged with messages can in turn have their perception of the world altered to better

align with these messages (Stacks & Salwen, 2014). This view is adopted primarily due to the

prominence and repetition of the message in question, allowing the consumer to better recall the

details of the message (Stacks & Salwen, 2014). An example of this effect would be a local news

network providing only stories about crime in the area, despite there being no spikes in crime

rates, making residents perceive that their city is plagued by a crime wave that is not actually

taking place.

Shrum (2002) posits that the vividness of a message also plays a distinct role in the recall

of a specific presentation or message:

Like frequency and recency, vividness has particular applicability to media effects. It

seems reasonable to think that television portrayals of particular actions and events may

be more vivid than real world experiences, given the drama-enhancing goal of

entertainment. (p. 73)

Given the immersive nature of these video games and depictions of events and people, it would

be logical to draw the conclusion that these games could be particularly effective in shaping

realities. Combining that vividness with the repetition of gameplay and the length of exposure to

these messages, with many games having a minimum of 10 hours of gameplay, it is easy to see

how consumers could adopt these representations.

When considering the application of cultivation theory to video game advertisements,

rather than the video games themselves, similar arguments towards applicability may be made.

Though the age of dominance may be coming to a close for television advertising, certainly


commercials for video games have yet to slow down. Today, you can find these ads promoted

online on a wide variety of social media sites. Sites such as Facebook and Twitter use ad

tailoring algorithms to deliver ads to the timelines of users who frequent video game related

subjects online. More notable, is the presence of these ads on YouTube. With the presence of

video game advertisements before and within videos related to video games, such as the wildly

popular category of ‘let’s play’ videos, it is easy to see how frequently gamers are exposed to

these ads.


CHAPTER II: REVIEW OF LITERATURE

The literature on games studies and representation, along with other topics unrelated to

violence in games, seems surprisingly sparse, considering the popularity of the media in

American culture (Williams, Martins, Consalvo, & Ivory, 2009; Burgess, Dill, Burgess, &

Brown, 2011; Fox & Tang, 2013; Keogh, 2014). However, it remains a viable and prolific area

of inquiry. This chapter presents the current literature on representation in gaming before

covering the tenants of the theoretical framework guiding this thesis. Finally, the chapter reviews

relevant literature on advertising.

Representation and Gaming

One article with particular relevance concerning representation in media and television

and its impacts is bell hook’s piece “The Oppositional Gaze.” In the article, the problematic

misrepresentation of Black women on television and the relative impact of those

misrepresentations are discussed at length. An example given early in the article considers the

television show “Amos n’ Andy,” noting the popularity of the show in the Black community,

while also noting how these White representations of Black identity are spectated through a

critical lens (hooks, 2003). This is not dissimilar to those experiences of non-White, non-male

consumers of video games as they step into a world built overwhelmingly from White male

perspective, as a study from 2005 found that around 83% of developers are White and around

88% are male (Gourdin, 2005). While it is unclear on how the racial demographics in game

development have shifted since that 2005 study, recent stats from Statista (2018) have shown

that as recently as 2016, women have improved to 23% of game developers versus men.


Moreover, hooks references one of her previous works, which analyzes the depiction of a

character in Amos N’ Andy, Sapphire, as a Black woman on television. As poorly framed as the

Black male characters were in this show, the Black female character (Sapphire) was perhaps

even more problematic. She filled a scapegoating role in which she was a target for everyone to

ridicule, which prompted some of the following responses from Black female viewers of the

syndicated series:

We all laughed at this Black woman who was not us. And we did not even long to be

there on the screen. How could we long to be there when our image, visually constructed,

was so ugly. We did not long to be there. We did not long for her. We did not long to be

this hated Black female thing - foil, backdrop. Her Black female image was not the body

of desire. There was nothing to see. She was not us. (hooks, 2003, p. 97)

This further cements the point made in that Williams and colleagues (2009) discussed regarding

how representation presents certain messages to those groups that consume this media, such as

not being considered important by greater society, which can lead to some very difficult

emotions with which to grapple.

Another consideration to make regarding the media effects of video games is the concept

of immersion. Unlike television and film, video games provide a feeling of active immersion

through integration that is measured through the degree by which that player feels integrated in

the game world (Taylor, 2002). Players can become deeply involved in a game as “an

experiential space,” which is described as intra-diegetic immersion (Taylor, 2002, p. 12). Simply

put, the very nature of these games can effectively make the player feel that they are building the

narrative of the game around them, concealing the true reality of that the game guides the player


along sets of variables predetermined by the developers. This can have some serious implications

on the impact of messages regarding misrepresentation on the player.

Though we now may understand the contents of the games to some degree, and just how

messages are divulged to players, it is important to discuss who these gamers are. According to

Fron, Fullerton, Morie, & Pearce (2007), the answer to this question has much to do with cultural

power structures. In their article, they looked at those persons who hold elite status within the

industry and noted that it is dominated almost entirely by White men. These elites decide what is

developed and published, and most importantly, for which players a game is designed or made.

This process has created the image of the “hardcore gamer” which the authors refer to as a

“rhetoric of play” that is exclusionary in nature, leaving out all those groups not protected by the

White male umbrella (p. 1).

Furthermore, the authors throw the metaphorical gauntlet down for scholars to not

proliferate the problematic rhetoric surrounding the hegemony of play, and for game designers to

challenge these assumptions in their work and develop for those audiences previously considered

others (Fron, Fullerton, Morie, & Pearce, 2007). If we are to change the way groups are or are

not represented in video games, just as any other media, it falls upon those who create and

normalize such products. The pool of individuals who choose to play games is rich and diverse,

and they deserve a pool of games and protagonists that reflects that rich diversity.

To better grasp how the demographics of video game consumers were understood by

those who market for these developers, one may turn to a more recent study on video games,

marketing, and diversity. Though approaches to video game development as late as the 1990’s

saw strong catering towards the male audiences in design and marketing (Fron, Fullerton, Morie,

& Pearce, 2007), newer games have made attempts to be more inclusive, at least in their


advertising. In a study published recently in 2016, a content analysis of video game commercials

airing in 2013 was conducted to ascertain the target demographic of the industry as a whole

(Chess, Evans, & Baines, 2016). This study filed the commercials under each of the major

gaming platforms and weighed the how these platforms represented age, gender, and racial

identity.

The year of 2013 was chosen for their analysis because it was a transitional year for home

console platforms, who were moving on to the next generation of consoles, and the authors

posited that a push for more inclusivity would be made at this juncture (Chess, Evans, & Baines,

2016). They were right in their supposition, apparently, as commercials that centered on the

subject of new consoles proved to have a more diverse cast of actors and actresses than

commercials that focused on content being released for the older consoles (p. 45). This is a

progressive step toward equality, but the authors noted that these commercials were still not

where they should be in terms of inclusivity, as it was discovered that though more women are

present in these commercials, no commercials featured women actually playing games, which

highlights a continued disconnect between the games industry and their consumer-base.

Aside from the findings that the next generation consoles had made a move towards

inclusivity, it was shown that Nintendo led the charge in a manner of speaking. In every category

that the researchers coded for diversity, racial, gender, and age representation, Nintendo proved

to be the most diverse on both their home system and handheld console. This is particularly

interesting when placed in conjunction with Fron, Fullerton, Morie, and Pearce’s (2007) study on

gender representations of video games’ marking materials. The authors had taken note that

Nintendo’s marketing featured more women, along with the rebranding of their system from

“Gameboy” to “DS,” and proposed the idea that through these practices, Nintendo could break


the video game industry away from what they referred in their article to as the “Hegemony of

Play” (p. 9).

This is not to say that developers only make games with protagonists who are White men,

as we see a few examples of minority groups represented throughout the history of video game

development, such as Ryo Hazuki from the critically acclaimed Shenmue series, Louis from the

Left 4 Dead series, Chell from the Portal series, and three of the four playable protagonists from

Borderlands: Mordecai, Roland, and Lillith. However, the question then comes back to the ways

that minority groups are represented. Jansz and Martis (2007) analyzed the heroine of the video

game “Tomb Raider” (Lara Croft) alongside a few other female protagonists. The authors found

that though female characters have found themselves in leading roles as strong protagonists, they

were predominantly White and were typically sexualized in their representation. This

sexualization was evident in their attire and in their body types, as coded by the researchers. It is

also worth noting that in the 12 games and 22 characters observed for this study, only eight

belonged to a racial group other than White, and of the 12 main characters, only three characters

were non-White (p. 145).

Their study shows that women can assume the position of power in these games, but it

does not free them from the male gaze of developers and consumers. This has deeper

implications for other minority groups as well. If racial minority characters are chosen as the

main roles, do they then face misrepresentation and problematic stereotyping as the female

protagonists faced sexualization? Perhaps those who make these games are not particularly the

correct fit for creating characters who accurately portray groups outside of their own racial or

ethnic identity.


A study completed by Taylor (2003) addressed the disconnect that sometimes forms

between the developer and the racial depictions in their video games. This is best highlighted by

a quote she gathered when pressing a developer about a particular artistic choice in the depiction

of non-Whites:

…when I inquired about why most of the heads were what we might think of as

Caucasian, why there were so few heads in this environment that had Asian or Black

features, I was given a fascinating (if not troubling) explanation by several people. As

one designer told me ‘If you color a white head white it looks white, if you color a black

head black it looks black… A few of them are built with deliberate racial characteristics

but I have found that coloring far and above colors, forgive the pun, how people see the

head rather than any given facial characteristics. (Taylor, 2003, p. 32)

The strangeness of this quote stems from a conversation earlier with these very designers on how

committed they were to provide a vision of diversity (2003). The only issue with this “vision” is

the superficial nature of the diversity. This shows how these designers can fall short of

understanding the nuances and importance of racial identity.

Without more diversity in the developer cycle, these types of mistakes must then be

expected to some degree. Developers will continue to make games primarily white and male so

long as those who work in the industry remain primarily white and male. Even with the best

intentions, if one is to rely on a designer to create a proper representation of a minority group

they are unfamiliar with, misrepresentation will happen. Just as bell hooks spoke of the male

gaze as an obstacle to proper representation of Black women in film and television (hooks,

2003), one must turn a critical eye to the developers of these games to address misrepresentation

and indeed lack of representation altogether.


Cultivation Theory

Cultivation theory focuses on the impacts of media messages on consumers. Gerbner,

Gross, Morgan, and Signorielli (1986) inform us that even a small shift in the cultivation of

perspectives, if sufficiently disseminated, can “alter the cultural climate and upset the balance of

social and political decision making without necessarily changing observable behavior” (p. 21).

Cultivation can be defined as “a pattern of operational practices that searches for relationships

between television exposure and a wide range of cultivation indicators” (Potter, 2014, p. 1015).

Keeping this in mind, and referring back to hooks, the underrepresentation of certain groups can

perhaps have a lasting effect on people’s perceptions of the relative inclusivity provided by video

game advertisements. Even worse, the cultivation of these perceptions could have a lasting

impact on how underrepresented groups perceive their own role in the greater landscape of

modern US culture.

One of the key assumptions of cultivation theory is that consumers of television

repeatedly exposed to a message are more likely to adopt or hold beliefs that mirror that message

(Littlejohn & Foss, 2009). In short, the inundation of mass media messages shapes the viewer’s

conception of their immediate reality. For example, a local news station regularly airing stories

about assaults in a specific locality may lead regular viewers of the broadcast to believe that their

region is experiencing a spike in assault related crime in the area. The applicability, however,

extends beyond violence and crime depictions on television. Generally, any question pertaining

to public opinion or perception on a specific concept may be explored through the lens of

cultivation theory (Littlejohn & Foss, 2009).


Ultimately, as Littlejohn and Foss explain, Shrum offers an explanation of the process of

cultivation and how it works, building upon the work Gerbner put into the founding of this

theory:

Simply put, he argues that most people do not give thoughtful answers to questions;

rather, they rely on whatever information seems readily available to them. They do not

systematically scan their memories for relevant information; rather, they take what is

most readily available. (2009, p. 256)

To speak metaphorically, cultivation theory has a lightning-rod effect, where viewers bombarded

with messages take the shortest path to a conclusion based on the most readily available

information. This, then, is the core of my theoretical framework as I argue that

underrepresentation of gender, age, and racial groups in video game advertising leads to an

immediate disassociation between those minority groups and the product in question.

A few studies using cultivation theory have been written prior to this study, including one

already covered earlier in my review of literature The Virtual Census, which helped to spark my

interest in this subject. In this study, Williams Martins, Consalvo, and Ivory (2009) explored

racial, gender, and age representation within video games, drawing implications regarding

impacts of under-representation of minority groups using Cultivation Theory. They found that

Latinx individuals, Native Americans, and older individuals were poorly represented, and

concluded that due to this low level of representation, players will be given the impression that

these groups are less visible than they truly are; in addition, they concluded that members of the

aforementioned groups may feel less important due to the lack of representation.

A more recent study on female representation in video games used cultivation theory to

explore the proliferation of problematic attitudes towards women (Kondrat, 2015). Specifically,


the author determined how video games may contribute to unhealthy or unnatural body ideals.

They ultimately concluded that representations of women were improving over time, thus

changing typical stereotyping of women (p. 189).

A similar study published in 2014 explored the impact of video game play on racial

stereotypes through cultivation research. The argument made by Behm-Morawitz and Ta (2014)

is that because representations of minority groups are so few in number, they are more likely to

be stereotyped, and that those stereotypes will then leave impressions on the gamer. The scholars

concluded that “time spent playing video games is predictive of White video game players’

beliefs about Blacks, such that greater frequency of play is linked to less favorable beliefs”

(Behm-Morawitz & Ta, 2014, pp. 11-12). As the scholars remind us, this agrees with the core

premise behind cultivation theory, where repeated exposure to a message shapes belief.

Outside of the realm of video games, there is much research that has been conducted

recently utilizing cultivation theory as a framework. In a study on media coverage on perceived

threats from Muslims, Khan and Bruschke (2016) employed the use of cultivation theory to

explain attitudes towards Muslims post September 11th. Using questionnaires, Khan and

Bruschke assessed total exposure to radio, television, and the internet in hours. This was then

weighed against the respondent’s perception of connectivity between media and fear. Finally,

this was compared with measures of perceived threat and intercultural contact.

Cultivation theory and its application to advertising was explored in a study which uses

the framework to evaluate gender representation in Philippine television ads. In the article,

Prieler and Centeno (2013) discussed how cultivation theory may lend to the greater discussion

on the reinforcement of gender roles and stereotypes due to the nature of stereotypical depictions

of gender in commercials. Although women were not underrepresented quantitatively in the


advertisements, the ways they were portrayed qualitatively were problematic. They highlighted

how the commercials tended to represent men and women:

settings in which more males were found in the workplace and more females were found

at home; the degree of dress, in which more males were fully dressed and more females

were suggestively dressed; voiceovers, which employed more males than females; and

product categories, in which cosmetics and toiletries were associated primarily with

female characters (Prieler & Centeno, p. 288).

Drawing from the framework, the authors concluded that these commercials continue to

perpetuate and entrench gender stereotypes.

One thing to consider regarding the applicability of cultivation theory in this thesis is the

media content this theory was developed to explore, and just how much the landscape has

changed today. This theory was developed to explore the impacts of television messages on

audiences, a media format that has since lost its dominance. In an article from Morgan,

Shanahan, and Signorielli (2015), the question of cultivation theory’s continued usefulness is

posited, considering the dramatic shift in media away from television and towards internet

content. In the article, an argument is made that cultivation’s continued survival is due in no

small part to the simple nature of its core assumption: “stories we tell (and are told) have

something to do with the way we think about the world” (Morgan, Shanahan, & Signorielli,

2015, p. 678). Simply put, cultivation may examine the relationship between a dependent

variable and exposure to content, which is the case, Morgan and his colleagues note, with many

current studies using this theoretical framework (Morgan, Shanahan, & Signorielli, 2015). The

method by which we receive stories is relatively unimportant when weighed against the content

of that message itself.


Potter (2014) offered a critical analysis of cultivation theory from a modern perspective.

In the article, criticism is thrown towards cultivation research which ignores the notion of time

when deciphering meaning in their findings. A particular emphasis is placed on the avoidance of

tackling “the degree to which those industrial produced meanings are widespread, the extent to

which the population is cultivated by those meanings, and the shape of those meanings’

influence over time” (Potter, 2014, p. 1030). Potter further argues that the current state of

cultivation research is mostly lackluster, that current literature ignores its origins in Gerbner and

instead “evolved into an exploratory forum for any type of media research as long as it looks at

some form of exposure to media content and looks for the relationship of that exposure to some

kind of effects outcome” (Potter, 2014, pp. 1031-1032). The article concludes by remarking that

for future research seeking to observe phenomena other than “macrolevel phenomena of media

influence on large aggregates over time” (Potter, 2014, p. 1032), then authors should look to

other theories regarding media effects which may have a better fit, or to develop newer theories,

rather than attempting to stretch cultivation theory too thinly.

There is indeed a sizable gap in literature regarding representation in video games (Fron,

Fullerton, Morie, & Pearce, 2007; Jansz & Martis, 2007; Williams, Martins, Consalvo & Ivory,

2009). Much of the work on video games has primarily concerned itself with the question of

violence and how the depictions in violent video games may influence players. Though this gap

has begun to be filled by many new enthusiastic scholars, there is still considerable space for

more research to be done.

As discussed in the Williams, Martins, Consalvo, and Ivory (2009) article, many studies

on video games have been limited due to small sample sizes. This thesis draws inspiration from

and expands upon the already uniquely situated article from the Chess, Evans, and Baines (2016)


on representation in video game commercials through the lens of cultivation theory. Due to these

two facts, this thesis seems to then find itself situated as the largest scale overview on

representation in video game advertising to date, poising itself as an important contributor to

cultivation theory as it applies to this subject.

Advertising

To better explore my choice of topic, we must look to scholarship on advertising as well.

According to Thorson and Rodgers (2012), advertising is defined as “paid communication from

an identified sponsor using mass media to persuade an audience” (p. 4). This is an important

distinction to make from other promotional tools, the editors of Advertisement Theory argue,

such as public relations, sales promotion, and personal selling (Rodgers & Thorson, 2012).

Understanding this distinction is fundamental for further reading on advertisement scholarship

and theory.

Something that also must be considered in comparing the advertising strategies of video

game consoles is that only Microsoft may be considered a domestic entity, with its headquarters

situated in Seattle Washington. Sony and Nintendo, in contrast, are Japanese companies, tasked

with marketing internationally. Taylor, Okazaki, and Mueller (2012) remind us that advertisers

must actively adjust marketing strategies to a degree dependent of their perceptions of similarity

and difference between their domestic market and the chosen international markets. This is a

tricky enough needle to thread when considering two western markets such as the United States

and Europe marketing internationally, but when considering an eastern to western marketing

adjustment, one may be safe in assuming that much more dramatic adjustments are required.

Another enlightening study from Aaker, Brumbaugh, and Grier (2000) highlights the

finding that Black individuals reacted more favorably to ads featuring Black actors than White


individuals did to seeing White actors in the same type of ad, which appeared to be directly

related to proportional minority status. One major implication we can draw from this study is that

cultivation theory proves to be an effective framework, seeing that there is measurable impact of

the representation of minority individuals in advertisements on those specific minority groups.

Further, a study on web browsers’ attitudes towards racially-targeted websites found that while

those with a stronger sense of ethnic identity show preference towards group representation, this

factor plays a minimal role in the response White individuals have towards these same ads, being

members of the majority (Appiah, 2004). The implication that may be drawn here is that there is

room for minority representation to become more diverse, as appealing to only the majority

group is less effective, it seems, than focusing even a little bit on the increasing of representation

of under-represented groups.

Finally, in the realm of advertising it is important for us to observe ethical considerations

within the industry and its professionals. In two separate studies, advertising professionals

consistently scored poorly on tests designed to gauge aptitude for ethical reasoning

(Cunningham, 2005; Wilkins & Coleman, 2005). Furthermore, these professionals were found to

have even lower scores in their ethical reasoning when presented issues from within their own

field of advertising (Cunningham, 2005). These shocking findings may help us to draw

conclusions regarding the rate of change over time in the issues of underrepresentation, as we

understand that the industry professionals are hesitant to identify such issues within their field

and work. Author of one of the aforementioned studies, Cunningham (2005), reasoned that this

hesitancy or disconnect was likely due to the professional’s focus on financial viability of the

solution of said problem.


Understanding on some level the motivations and innerworkings of advertising, as stated

earlier in this review of literature, will help to focus the findings of this thesis and indeed provide

a degree of reasoning for trends that may or may not be present. This, combined with the

research conducted on video games and representation presented in the literature review will

help to guide this thesis and inform any implications drawn in the data analysis and discussion.


CHAPTER III: RESEARCH QUESTIONS AND METHODOLOGY

This thesis aims to serve as a step in the right direction in the research of video games as

a cultural phenomenon, helping to place it on the same stage as television, radio, and film. As a

salient media text in modern society, it is important that we understand, or seek to understand,

the contexts surrounding the text, the effects of the text, and the text itself from a communication

perspective.

There are a multitude of reasons why a study like this has yet to be performed. The first

reason relates to the scale of the project. Considering the size of the population sampled

combined with the nature of a study observing a span of fifteen years, most scholars would rather

opt to do a snapshot study of the industry today, rather than viewing the larger context of

progression. Secondly, this study has yet to be done due to lack of interest in this particular

aspect of the video game industry. Games studies is a growing field of scholarship (Chess,

Evans, & Baines, 2016; Williams, Martins, Consalvo, & Ivory, 2009), with important research

being contributed every day, but much of that research is focused on effects of video game

usage, representation within video games themselves, and content of said video games. As such,

the methods by which companies advertise their products have taken a back seat. Lastly this has

not yet been studied likely due to lack of insight, or common perceptions of the current state of

the industry. In much of the literature surrounding video games, many claims or assumptions are

made regarding the state of representation in video game marketing, but not much in the way of

evidence to back these claims. There is not much of a reason to study diversity when the

dominant thought surrounding the industry already criticizes lack of diversity. Hopefully the

results of this study will better inform those assumptions and claims.


Research Objectives

To address whether the concerns regarding diversity and inclusivity in the video game

industry continues to evolve, more targeted research must be conducted on advertisements that

surround these games. This study approaches these advertisements to ascertain how racial,

gender, and age representation in video game console commercials has shifted over to provide

some perspective on where the industry was 15 years ago, where it is now, and where it may be

going forward if they continue their respective trends. This project features three research

questions:

RQ1: To what extent are gender, racial, and age identities represented in advertisements

for consoles produced by Microsoft, Nintendo, and Sony?

RQ2: To what extent are gender, racial, and age identities represented in advertisements

for consoles between 2003 and 2017?

RQ3: How do Microsoft, Nintendo, and Sony differ in their representations of racial,

gender, and age identity over time from 2003 and 2017?

Methodology

This project features a content analysis of video game console advertisements produced

by three major companies (i.e., Microsoft, Nintendo, and Sony) between 2003 and 2017. The

sample was further restricted by parameters which follow. The commercials must be for consoles

produced by Sony, Nintendo, or Microsoft and must also feature human actors or characters with


discernable features, which is to say that games that only feature non-human characters, or

characters with undefined racial, gender, or age identities (e.g., due to obstructions such as

armor) will be cast aside.

These commercials were pulled from the same archive used in the What does a gamer

look like article, Gamepressure.com (Chess, Evans, Baines, 2016). According to the

Gamepressure (2017) archive, there are a total of 431 commercials in the population for the

selected time frame of 2003-2017. However, only 234 commercials featured human characters.

To trim the sample into a more manageable size, the commercials were first separated into the

three categories of Microsoft, Sony, and Nintendo, before being further separated into three-year

blocks (2003-2005, 2006-2008, 2009-2011, 2012-2014, 2015-2017) at which time simple

random samples were taken from each category. For each company, Microsoft, Sony, and

Nintendo, four commercials were sampled from each block, which brought the target total for the

sample to 75 commercials. Unfortunately, Microsoft had some missing data from the first two

time periods, leaving the total sample at 71 commercials. This was the best, most representative

sample attainable due to missing data from Microsoft, as they only have 3 valid commercials in

the 2003-2005 period and 3 valid commercials in the 2006-2008 Time Period. Expanding these

data any further could potentially skew data due to the difference in weighting between the

companies observed.

This was the most effective framework for my study primarily due to the fact that this

time-frame allows me to observe three generations of consoles. Generations used in this manner

refers to the rhythm in which consoles are released, as competitors typically release about every

five years and within one year of each other.


Units of Analysis

As this study was a quantitative content analysis on commercials that vary in content, my

units of analysis had to both be as flexible and clearly defined as possible. For the purpose of

describing the units of analysis, it would be best to first describe the two types of commercials

observed. The first of these commercial categories is live action, or more accurately defined:

commercials which feature live actors, depicted as players of a video game. The other

commercial category is more concerned with the video game itself, and as such is defined by

either live or computer-generated actors, depicting characters of a video game.

The recording units for this thesis, to be clear, are those persons or characters that appear

on screen through the course of the commercial. The methodology for this thesis is informed by

Chess, Evans, and Baines’s (2016) article, What Does a Gamer Look Like? Video Games,

Advertising, and Diversity as a model for my analysis, as it performs a similar type of content

analysis as this thesis seeks to perform, only they limit themselves to only commercials released

in 2013, while also looking at behaviors. Drawing inspiration from this article, this thesis uses

three measurement classifications: game platform, year of release, and physical characteristics of

gamer or character.

Codes

Video game company. As the time frame covered multiple iterations of consoles, the

variables for platform limit themselves to just the names of the companies who develop each of

the three major platforms: Microsoft, Sony, and Nintendo.

Year. Year of release is mostly self-explanatory, as each of these commercials were

coded by year of original air date. This is important to distinguish as certain advertising


campaigns for single product may have commercials that have original air dates in two adjacent

years. Additionally, commercials may run for multiple years after its original air date. The

variables as defined here, 2003-2017, are both mutually exclusive and exhaustive.

Racial, gender, and age representation. The final measure, physical characteristic of

gamer/character, is where we find the most important part of the study. As addressed in the What

Does A Gamer Look Like article, coding racial identity in commercial advertisements is often

difficult do to a lack of biographical information regarding the actors. As Chess, Evans, and

Baines describe:

everything in television commercials is about perception while the real age or ethnicity of

an actor might be disguised by clothing style or makeup, it is only the perception of their

age and ethnicity that carries meaning in the fifteen to thirty seconds that we consume the

commercial. Thus, using a content analysis method wherein we are able to track multiple

visual perceptions about factors such as age, ethnicity, and gender allows us to consider

the tricky space of how the audience is most likely to perceive these characters. In other

words, it does not necessarily matter if an actor is a thirty-five-year-old African American

woman; what matters is how she visually parses to audiences in a short period of time.

(2016, pp. 4-5)

Keeping this in mind, two trained researchers coded age, gender, and racial identity based on

perception. In each of the following categories, labels were included for characters which the

coders were unable to identify for any reason, such as the quality of the video or obscuration of

face or features, which is referred to as “cannot discern.” For the racial category, using the US

census as inspiration, the variables used were White, Black or African American, Native

American or American Indian, Hispanic or Latino, Arab American, Asian or Pacific Islander,


cannot discern or other. For age, the following variables were used: Pre-adolescent, adolescent,

adult, middle age, older adult, and cannot discern. Pre-adolescent included any character clearly

under teenage, adolescent included characters between 13 and 18, or clearly high school aged

individuals. Adults were characters who were 19 to mid-30’s, middle aged around mid-30’s to

60’s, and older adults around mid-60’s and up. Lastly, for gender, individuals will be coded as

either man, woman, trans, or cannot discern. Labels used for each code were drawn from similar

literature dealing with demographics, lifespan development research, and commonly accepted

census categories used by the US census (Heckhausen, Dixon, & Bates, 1989; McCrae et al.,

2000; U.S. Census Bureau, 2017; Williams, Martins, Consalvo, & Ivory, 2009; Williams,

Ponesse, Schachar, Logan, & Tannock, 1999).

Role. Lastly, the characters were coded as either primary or secondary, which is

determined by their perceived role in the commercial. For commercials depicting gamers playing

on a console, primary status is determined by who is depicted as the player, while in

commercials that depict the game characters themselves, Primary character is determined by

perception of role by the coders. Each of the categories being observed, as listed above, along

with their conceptual definitions are contained in the code handbook which was prepared to

coding and is included in this document as Appendix A.

Collection Procedure

Two trained scholars (i.e., a graduate researcher and I) coded the data. Time was taken

prior to the coding process to train the outside coder on the methods of this project, to ensure that

he understood expectations for the data they are to collect. The training process consisted of first

spending time to look through the conceptual definitions and exemplars provided in the prepared

code handbook (Appendix A), before familiarizing that second coder with the coding worksheet


developed for ease of use in data collection, which has been included in this document as

Appendix B. From there, I walked through the process of coding using a commercial, showing

how I would code each character. Afterwards, we walked through a commercial together where

the other coder will code alone and walk me through their process, unpacking reasoning and

motivation where applicable. Finally, we went through a few commercials and coded separately,

comparing notes afterwards. The purpose of this final step was to buff out complications and

disconnections that appeared between the two coders and worked out a common interpretation

on which both agreed. The entire process took around three hours.

Intercoder reliability was calculated using Cohen’s Kappa after coding the first 20% of

the target sample. Cohen’s Kappa determined a reasonable level of consistency and agreement

between the two coders in each category; traditionally, a value greater than .70 is an acceptable

level of intercoder reliability. A sufficient level of intercoder reliability was achieved after one

round of preliminary coding. Role scored as .873 with p<.001, racial identity scored as .87 with

p<.001, Gender scored 1.0 with p<.001, and age scored .78 with p<.001. The rest of the target

sample was divided evenly between the two coders, with 28 commercials going to each coder.


CHAPTER IV: DATA ANALYSIS AND RESULTS

Data Analysis

Ultimately the goal of this thesis is to track the trajectory of the entire video game

industry and to determine whether it is becoming more or less diverse in its marketing. However,

the thesis also aims to analyze how the three major companies in the industry measure up to one

another. To that end, the data collected regarding diversity was sorted by platform and year of

release. This organization allowed visibility of where each of these companies ranked, by year,

in their attempts at diversity and inclusivity. Because the data were nominal in nature, a series of

chi square analyses were performed. This analysis allowed observation and identification of

relationships between the specific companies and diversity in commercials while taking into

consideration the year of release.

Results

The aim of this project was to determine if there were systematic differences in racial,

gender, and age representations in video game console commercials produced by Microsoft,

Nintendo, and Sony from 2003 to 2017. Three research questions were posed: To what extent are

gender, race, and age identities represented in advertisements for video game consoles produced

by Microsoft, Nintendo, and Sony? To what extent are gender, race, and age identities

represented in advertisements for consoles between 2003 and 2017? How do Microsoft,

Nintendo, and Sony differ in their representations of racial, gender, and age identity over time

from 2003 and 2017?


In this chapter, the project’s overall data will be described before presenting the statistical

results affiliated with each research question. First, how gender, racial, and age representation

varied across the three video game companies will be covered. Second, how gender, racial, and

age representations differed across the project’s five-Time Periods will be highlighted. Lastly,

the results of the analyses to explain how each company differed in their representation of

gender, racial, and age identities over the five-Time Periods will be presented.

The Big Picture: Describing the Project’s Data

The coders reviewed 70 total commercials, containing 392 characters. Of those

characters, 297 where White, 44 were Black, 18 were Asian or Pacific Islander (API), 7 were

Latinx, and 5 were Arab American with 21 individuals who the coders were unable to identify

due to obstruction of features in the advertisments. Looking at gender, 244 individuals were

coded as men, 139 as women, and 9 were left unable to identify. A total of 36 characters were

coded as pre-adolescent, 42 as adolescents, 236 as adults, 38 as middle age, 19 as older adults,

and 21 were unable to be identified. Those in each category that were unable to be identified are

referred to in the figures that follow as Gender NI, Race NI, and Age NI respectively.

The distribution of these characters among each of the companies was 114 in Microsoft,

148 in Nintendo, and 130 in Sony. Among time periods the distribution of characters was 110 in

Time Period 1, 101 in Time Period 2, 83 in Time Period 3, 42 in Time Period 4, and 87 in Time

Period 5. A closer examination of the data reveals important patterns in the representation of

racial, gender, and age identity across the study’s Time Periods and selected video game

companies’ commercials. The next section explains how Microsoft, Sony, and Nintendo differed

in the ways they represented gender, racial, and age identity.


Gender, Racial, and Age Representations by Company

To answer the first research question, a series of chi-square analyses was conducted. As

defined by Singleton and Straits (2004), a chi-square test is “based on a comparison of the

observed cell frequencies with the cell frequencies one would expect if there were no

relationship between the variables” (p. 470). This method is used due to the nature of the data

being observed and the nature of the research being done, as this thesis seeks to identify

variances in expected trends. These analyses examined data points at the intersections of gender,

racial, and age representation with each of the three companies. What follows are trends and

insights revealed by that analysis, answering RQ1.

Gender representation. Examining how gender representations differed across the three

platforms, it was found that of the 114 characters in Microsoft advertisements, 72 were men and

40 were women. Of the 148 characters that appeared in the Nintendo advertisements, 90 were

men, while 56 were women. Finally, of the 130 characters shown in the Sony advertisements

observed, 82 were men, and 43 were women.

Running a chi-square analysis on the representation of gender across the three companies

revealed that while men were disproportionately overrepresented, there was no statistically

significant difference, χ2(4) = 2.609 p =.625, in the gendered representation from one company to

another (Table 1). In other words, all three companies overrepresented men at a similar rate. In

this category, 70 ads were examined with a total of 392 characters. A bar chart illustrating these

data can be seen in Figure 1.


Table 1. Chi-Square Analysis of Differences in Gender

Representation by Company

Asymptotic Significance Value df (2-sided)

Pearson Chi-Square 2.609 4 .625

Likelihood Ratio 2.490 4 .646

Linear-by-Linear

Association .293 1 .588

N of Valid Cases 392

Figure 1. Differences in Gender Representation by Company


Racial representation. Looking at racial representation, it was found that the distribution

of characters in Microsoft advertisements were 93 White, 10 Black, three Arab American, one

Latinx, and zero Asian or Pacific Islander. In the Nintendo commercials, 116 of the characters

were White, 12 were Black, 11 were Asian or Pacific Islander, two were Latinx, and one was

Arab American. Lastly, Sony saw a distribution of 88 White, 22 Black, seven Asian or Pacific

Islander, four Latinx, and one Arab American.

A chi-square analysis examining racial representations across the three companies

revealed that white characters were grossly overrepresented, making up 75.8% of characters

observed. There was significance, χ2 (10) = 20.40, p = .026, in the differences between how the

three companies approached representation (Table 2). Differences highlighted include total lack

of Asian representation and the lack of any significant Latinx representation in Microsoft

commercials. Another difference shown is the Black representation from Sony, being

significantly higher than the other two companies. These differences in representation are

highlighted in a bar chart which can be seen in Figure 2.


Table 2. Chi-Square Analysis of Differences in Racial

Representation by Company




Linear-by-Linear

Association 2.406 1 .121


Figure 2. Differences in Racial Representation by Company


Age representation. In the third category, age, it was found that found that of the

characters that appeared in Microsoft commercials, 73 were adult, 18 were middle age, 14 were

adolescent, two were older adults and zero were pre-adolescent. Of those who appeared in

Nintendo commercials, it was found that 62 were adult, 32 were pre-adolescent, 20 were

adolescent, 15 were middle age, and 14 were older adults. Finally, of those who had appeared in

Sony advertisements, 101 were adult, eight were adolescent, five were middle age, four were

pre-adolescent, and three were older adults.

A chi-square analysis that examined age representations across the three companies

found that adults were overrepresented compared to other age groups, making up 60.2% of the

total of characters observed. Significance was established, χ2 (10) = 80.94, p < .001, indicating

that there was indeed a difference in the way age was represented among the three consoles

(Table 3). One difference highlighted in the analysis Sony’s avoidance of age groups outside of

adults. Sony had the highest rates of adult representation and the lowest in each of the other

groups. Another difference highlighted was Nintendo’s cornering on older adults and pre-

adolescent representation. can be seen in Figure 3.


Table 3. Chi-Square Analysis of Differences in Age

Representations by Company




Linear-by-Linear



Figure 3. Differences in Age Representation by Company


Gender, Racial, and Age Representations by Time Period

To answer the second research question, chi-square analyses were performed to examine

how gender, racial, and age identities were represented across the study’s five Time Periods:

2003-2005, 2006-2008, 2009-2011, 2012-2014, and 2015-2017. What follows are trends and

insights revealed by those analyses, answering RQ2.

Gender representation. Examining how gender representation differed over time, of the

79 characters that appeared in advertisements between 2003 and 2005, 59 were men, and 18

were women. Of the 101 characters that appeared in advertisements between 2006 and 2008, 54

were men and 44 were women. Of the 83 characters that appeared in advertisements between

2009 and 2011, 48 were men, and 33 were women. Of the 42 characters that appeared in

advertisements between 2012 and 2014, 30 were men, and 10 were women. Of the 87 characters

that appeared in advertisements between 2015 and 2017, 53 were men and 34 were women.

These descriptive statistics are presented in Figure 4.

A chi-square analysis that compared gender representations across the five-Time Periods

revealed that women made up just over a third of all characters observed at 35.5%. Thus, women

were generally underrepresented in the advertisements from 2003 to 2017. Marginal significance

was determined, χ2 (8) = 15.214, p = .055, pointing to slight variances in representation (Table

4), with the largest difference being between the first two Time Periods of 2003 to 2005 and

2006 to 2008. During these two periods, the gap between the representation of men and women

was significantly smaller than other periods. Differences present between Time Periods can be

seen in Figure 4.


Table 4. Chi-Square Analysis of Differences in Gender

Representation Over Time




Linear-by-Linear



Figure 4. Differences in Gender Representation Over Time


Racial representation. Examination of racial representation over time found that of the

characters appearing between 2003 to 2005, 59 were White, 11 were Black, three were Asian or

Pacific Islander, two were Latinx and zero were Arab American. Of the characters appearing

between 2006 and 2008, 80 were White, eight were Black, eight were Asian or Pacific Islander,

one was Latinx, and zero were Arab American. Of the characters appearing between 2009 and

2011, 67 were White, six were Black, three were Asian or Pacific Islander, two were Arab

American, and zero were Latinx. Of the characters appearing between 2012 and 2014, 31 were

White, eight were Black, two were Asian or Pacific Islander, zero were Latinx and zero were

Arab American. Of the characters appearing between 2015 and 2017, 60 were White, 11 were

Black, four were Latinx, three were Arab American, and two were Asian or Pacific Islander.

A chi-square analysis that examined racial representations across the five Time Periods

revealed that white representation consistently made up a majority of the total characters observed

ranging from 69% to 80.7%. There were assorted micro-variances in other observed categories,

however significance was not determined, χ2 (20) = 25.726, p = .175, as seen in Table 5.



Representation Over Time




Linear-by-Linear



Figure 5. Differences in Racial Representation Over Time


Age representation. Looking at how age was represented over time it was found that of

the characters appearing between 2003 and 2005, one was pre-adolescent, seven were

adolescent, 48 were adult, 12 were middle age, and six were older adults. Of the characters

appearing between 2006 and 2008, 12 were pre-adolescent, 10 were adolescent, 57 were adult,

10 were middle age, and nine were older adults. Of the characters appearing between 2009 and

2011, three were pre-adolescent, 13 were adolescent, 50 were adult, 11 were middle age, and two

were older adults. Of the characters appearing between 2012 and 2014, four were pre-adolescent,

two were adolescent, 32 were adult, zero were middle age, and zero were older adults. Of the

characters appearing between 2015 and 2017, 16 were pre-adolescent, 10 were adolescent, 49

were adult, five were middle age, and two were older adults.

A chi-square analysis that examined age and time revealed that while adult representation

far outweighed other observed categories, variances in other observed categories were

determined to be significant, χ2 (20) = 43.481, p = .002, as shown in table 6. Differences

highlighted, such as the spikes in representation of pre-adolescents from 2006 to 2008, and from

2015 to 2017, and the dip in representation of adolescents, middle aged, and older adult

individuals from 2012 to 2014 can be seen in Figure 6.


Table 6. Chi-Square Analysis of Differences in Representations

of Age Over Time.




Linear-by-Linear



Figure 6. Differences in Representations of Age Over Time


Gender, Racial, Age Representations by Company Over Five Time Periods

To answer the third research question, a series of chi-square analyses were run to

examine data points at the intersections of gender, racial, and age representation with each of the

three companies over the five Time Periods; 2003 to 2005, 2006 to 2008, 2009 to 2011, 2012 to

2014, and 2015 to 2017. What follows are trends and insights revealed by those analyses,

answering RQ3.

Gender representation. Examining representations of gender in Microsoft commercials

over time, of the characters appearing from 2003 to 2005, there were 28 men and six women. Of

the characters appearing from 2006 to 2008, there were 14 men and 17 women. Of the characters

appearing from 2009 to 2011, there were seven men and 10 women. Of the characters appearing

from 2012 to 2014, there were 11 men and two women. Of the characters appearing from 2015

to 2017, there were 12 men and five women.

A chi-square analysis run on the intersection of gender representation in Microsoft

commercials and Time Period that revealed that men were represented more than women in

three-Time Periods, χ2 (8) = 17.790, p = .023 (see Table 1). Differences highlighted, such as the

reduced representation of men from Time Period 1 to Time Period 2, and the representation of

women overtaking representation of men in Time Period 2 and 3 may be observed in Figure 7.


Table 7. Chi-Square Analysis of Differences in

Representations of Gender by Microsoft Over Time

Asymptotic Significance Value df (2-sided) Pearson Chi-Square 17.790 8 .023


Linear-by-Linear



Figure 7. Differences in Representations of Gender by Microsoft Over Time


Examining representations of gender in Nintendo commercials over time, of the

characters appearing from 2003 to 2005 the distribution was eight men and two women. Of the

characters appearing between 2006 and 2008, the distribution was 34 men and 21 women. Of the

characters appearing between 2009 and 2011, the distribution was 18 men and nine women. Of

the characters appearing between 2012 and 2014, the distribution was nine men and six women.

Of the characters appearing between 2015 and 2017 the distribution was 21 men and 18 women.

A chi-square analysis that examined the gender representation in Nintendo commercials

and Time Period revealed no significance, χ2 (8) = 12.119, p = .146, as seen in Table 8

immediately below. Following Table 8, the data analysis is detailed in Figure 8.

Table 8. Chi-Square Analysis of Differences in

Representations of Gender by Nintendo Over Time




Linear-by-Linear




Figure 8. Differences in Representations of Gender by Nintendo Over Time

Examining representations of gender in Sony commercials over time, of the characters

appearing from 2003 to 2005 the distribution was 23 men and 10 women. Of the characters

appearing from 2006 to 2008 the distribution was six men and six women. Of the characters

appearing from 2009 to 2011 the distribution was 23 men and 14 women. Of the characters

appearing from 2012 to 2014 the distribution was 10 men and two women. Of the characters

appearing from 2015 to 2017 the distribution was 20 men and 11 women.

A chi-square analysis run on the intersection of gender representation in Sony

commercials and Time Period revealing no significance in the data, χ2(8) = 10.60, p = .225, as

seen in Table 9 immediately below. Following Table 9, the data analysis is detailed in Figure 9.


Table 9. Chi- Square Analysis of Differences in Representations

of Gender by Sony Over Time



Linear-by-Linear



Figure 9. Differences in Representations of Gender by Sony Over Time


Racial Representation. Examining racial representation in Microsoft commercials over

time, of the characters appearing from 2003 to 2005 the distribution was, 29 White, two Black,

zero Latinx, and zero Arab American. Of the Characters appearing from 2006 and 2008, the

distribution was 28 White, two Black, zero Latinx, and zero Arab American. Of the characters

appearing between 2009 and 2011, the distribution was 17 White, zero Black, zero Latinx, and

zero Arab American. Of the characters appearing between 2012 and 2014, the distribution was

13 White, zero Black, zero Latinx, zero Arab American. Of the characters appearing between

2015 and 2017, the distribution was six White, six Black, one Latinx, and three Arab American.

A chi-square analysis run on the intersection of racial representation in Microsoft

commercials and Time Period. This analysis revealed significance, χ2 (16) = 48.99, p < .001, in

the differences found between categories observed (Table 10). One trend observed was a sharp

and consistent decrease in White representation from Time Period 1 to Time Period 5. A spike in

Black and Arab American representation in the fifth Time Period is also observed, with the

Black representation becoming equivalent to White representation. These observations are

highlighted in Figure 10.



Representation by Microsoft Over Time



Linear-by-Linear



Figure 10. Differences in Racial Representation by Microsoft Over Time


Examining racial representation in Nintendo commercials over time, of the characters

appearing from 2003 to 2005 the distribution was 11 White, zero Black, zero Latinx, zero Arab

American, and zero Asian or Pacific Islander. Of the characters appearing from 2006 to 2008 the

distribution was 42 White, four Black, 1 Latinx, zero Arab American, and seven Asian or Pacific

Islander. Of the characters appearing from 2009 to 2011 the distribution was 23 White, one

Black, zero Latinx, one Arab American, and zero Asian or Pacific Islander. Of the characters

appearing from 2012 to 2014 the distribution was eight White, five Black, zero Latinx, zero Arab

American, and two Asian or Pacific Islander. Of the characters appearing from 2015 to 2017 the

distribution was 32 White, two Black, one Latinx, zero Arab American, and two Asian or Pacific

Islander.

A chi-square analysis examining racial representations in Nintendo commercials showed

no significance, χ2 (20) = 28.77, p = .092, in differences present in data as seen in Table 11




Representation by Nintendo Over Time



Linear-by-Linear



Figure 11. Differences in Racial Representation by Nintendo Over Time


Examining racial representation in Sony commercials over time, of the characters

appearing from 2003 to 2005 the distribution was 19 White, nine Black, two Latinx, zero Arab

American, and three Asian or Pacific Islander. Of the characters appearing from 2006 to 2008

the distribution was 10 White, two Black, zero Latinx, zero Arab American, and one Asian or

Pacific Islander. Of the characters appearing from 2009 to 2011 the distribution was 27 White,

five Black, zero Latinx, one Arab American, and three Asian or Pacific Islander. Of the

characters appearing from 2012 to 2014 the distribution was 10 White, three Black, zero Latinx,

zero Arab American, and zero Asian or Pacific Islander. Of the characters appearing from 2015

to 2017 the distribution was 22 White, three Black, two Latinx, zero Arab American, and zero

Asian or Pacific Islander.

A chi-square analysis examining racial representations in Sony commercials and Time

Period revealed that there was no significance, χ2 (20) =19.98, p = .459, in data collected, as seen

in Table 12 immediately below. Following Table 12, the data analysis is detailed in Figure 12.


Table 12. Chi- Square Analysis of Differences in Racial

Representation by Sony Over Time



Linear-by-Linear



Figure 12. Differences in Racial Representation by Sony Over Time


Age representation. Examining representations of age in Microsoft commercials over

time, of the characters appearing from 2003 to 2005 the distribution was zero adolescent, 21

adult, eight middle age, and one older adult. Of the characters appearing from 2006 to 2008,

three were adolescent, 24 were adult, three were middle age, and one was an older adult. Of the

characters appearing between 2009 and 2011 the distribution was seven adolescent, three adult,

seven middle age, and zero older adults. Of the characters appearing from 2012 to 2014, the

distribution was one adolescent, 12 adult, zero middle age, and zero older adults. Of the

characters appearing from 2015 to 2017, the distribution was three adolescent, 13 adult, zero

middle age, and zero older adults.

A chi-square analysis examining age representation in Microsoft commercials over time

revealed significance, χ 2 (16) = 46.26, p <.001, in data collected, as shown in Table 13. Two

largely observable trends were the drop in adult representation in Time Period three and the loss

of representation in middle age in Time Period four and Time Period 5. Another observation that

may be made is the spike in adolescent representation in period 3, which drops off in periods 3

and 4. These trends may be seen in Figure 13.



of Age by Microsoft Over Time



Linear-by-Linear



Figure 13. Differences in Representations of Age by Microsoft Over Time


Examining representations of age in Nintendo commercials over time, of the characters

appearing from 2003 to 2005 the distribution was zero pre-adolescent, two adolescent, three

adult, two middle age, and four older adults. Of the characters appearing from 2006 to 2008 the

distribution was 12 pre-adolescent, seven adolescent, 21 adult, seven middle age, and eight older

adults. Of the characters appearing from 2009 to 2011 the distribution was zero pre-adolescent,

six adolescent, 14 adult, four middle age, and two older adults. Of the characters appearing from

2012 to 2014 the distribution was four pre-adolescent, one adolescent, eight adult, zero middle

age, and zero older adults. Of the characters appearing from 2015 to 2017 the distribution was 16

pre-adolescent, four adolescent, 16 adult, two middle age, and zero older adults.

A chi-square analysis run on the intersection of age representation in Nintendo

commercials and Time Period revealed significance (χ 2 (20) = 52.37, p < .001) in data collected

as shown in Table 14. Figure 14 depicts trends found in the analyzation of these data. One trend

observed is the small gap in representation between all groups in Time Period 1 before a massive

spike in adult representation in Time Period 2, which stays as a constant moving forward.

Another trend observed is a drop in other groups outside of adults before a large spike in pre-

adolescent in Time Period 5, where the group evens out with adult cases of representation.



of Age by Nintendo Over Time



Linear-by-Linear



Figure 14. Differences in Representations of Age by Nintendo Over Time


Examining representations of age in Sony commercials over time, it was found that of the

characters appearing from 2003 to 2005 the distribution was one pre-adolescent, five adolescent,

24 adult, two middle age, and one older adults. Of the characters appearing from 2006 to 2008

the distribution was zero pre-adolescent, zero adolescent, 12 adult, zero middle age, and zero

older adults. Of the characters appearing from 2009 to 2011 the distribution was three pre-

adolescent, zero adolescent, 33 adult, zero middle age, and zero older adults. Of the characters

appearing from 2012 to 2014 the distribution was zero pre-adolescent, zero adolescent, 12 adult,

zero middle age, and zero older adults. Of the characters appearing from 2015 to 2017 the

distribution was zero pre-adolescent, three adolescent, 20 adult, three middle age, and two older

adults.

A chi-square analysis run on the intersection of age representation in Sony commercials

reveals no significance, χ2 (20) = 28.39, p = .100, in the data collected as seen in Table 15




of Age by Sony Over Time




Linear-by-Linear



Figure 15. Differences in Representations of Age by Sony Over Time


CHAPTER V: DISCUSSION

Drawing from the framework of cultivation theory, the goal of this study was to analyze

the racial, gender, and age representations of Microsoft, Nintendo and Sony’s video game

console commercials airing between 2003 and 2017. This thesis addressed three research

questions: To what extent are gender, racial, and age identity represented in advertisements for

consoles produced by Microsoft, Nintendo, and Sony? To what extent are gender, racial, and age

identity represented in advertisements for consoles between 2003 and 2017? How do Microsoft,

Nintendo, and Sony differ in their representations of racial, gender, and age identities over time

from 2003 and 2017? In this chapter, the key findings and implications of my project are first

highlighted.

With the frequency at which gamers are exposed to these ads every day while browsing

the internet, certainly cultivation theory would conclude that the audience may adopt these

depictions and representations of racial, gender, and age identities. YouTube is, in fact the

second most visited site on the internet (Alexa, 2018). In a Google commissioned Nielson study

in 2015, it was found that on mobile browsing alone, YouTube reaches more 18 to 49 year-olds

than any broadcast or cable television network (O’Neil-Hart & Blumenstein, 2016). Further, it

was found in another Nielsen study that in an average month, eight out of ten 18 to 49 year-olds

watch YouTube and another similar study found that in 2015 this demographic has seen a drop

of 4% in watch time on television while time spent on YouTube has increased by 74% (O’Neil-

Hart & Blumenstein, 2016). In total, this comes out to 1.5 billion active monthly users (Matney,

2017), watching one billion hours of YouTube per day (Etherington, 2017). In another article

using Google analytics, Petrova and Gross highlight that 73% of YouTube users who identify as

gamers say that they enjoy watching people play games on the platform, while 48% claim they


watch more gaming videos on the site than they spend actually playing games themselves

(2017). With the combination of pre-roll and mid-roll ads that play on every YouTube gaming

video, it is nearly impossible to avoid constant exposure when watching 30 to 60 minute long

let’s play videos, or three-hour long stream archives.

Key Findings and Implications

Examining differences in racial, gender, and age representations by video game

company. RQ1 asked to what extent are gender, racial, and age identities represented in

advertisements for consoles produced by Microsoft, Nintendo, and Sony. It was found that across

all three companies, men were vastly overrepresented compared to women. However, the

overrepresentation of men in video game console commercials did not differ systematically

among Microsoft, Nintendo, and Sony. That said, there were significant differences present in

the companies’ representations of racial and age identity. The coded data show that none of the

companies had any instances of Native American representation in the sample’s commercials,

along with minimal instances of Asian or Pacific Islander, Latinx, or Arab individuals. Microsoft

had no representations of Asians or Pacific Islanders in this project’s sample, meaning the total

representation of Asian persons were divided between Nintendo and Sony at 61.1% (n=11) and

38.9 % (n=7) respectively. In addition, Sony commercials made up 50% of all Black

representation observed (n=22), and 57.1% of all Latinx representation observed (n=4). White

representation was still dominant in Sony commercials, but only made up 67.7% of characters

observed (n=88) in the company’s advertising versus Microsoft’s White characters at 81.6% of

the total population (n=93) and Nintendo’s White characters at 78.4% of the total population

(n=116).


Non-dominant groups, if represented at all, were severely underrepresented in

comparison to white representation in the scope of all advertisements from each of the three

companies observed. While racial representation differed from company to company, with Sony

showing the most racial diversity, when looking at 15 years of commercials, any frequency under

15 people indicated that there was less than one instance of representation per year on average,

which is the case for all non-White representation other than Sony’s representation of Black

individuals.

The major implication that can be drawn from this using the framework of cultivation

theory would be that these minority groups in the category of racial identity may feel that the

industry has ignored them, or that they are not important to the success of these consoles, as the

ads do not target them. The other implication that we may draw is that the low visibility of these

minority groups implies to avid gamers that these groups are not a part of gaming culture,

creating an unwelcoming atmosphere in the greater culture. Similar implications were drawn in

the article from Williams, Martins, Consalvo, and Ivory (2009), in their comprehensive content

analysis of video games released between March of 2005 and February of 2006. These

implications are drawn directly from the core tenet of cultivation theory, that states that the more

an audience is exposed to a message, the more that audience tends to shape their reality around

said message.

This implication may also be drawn regarding age representations across the three

companies observed. Sony was the worst of three companies in this regard; adults made up

77.7% of all characters present in their advertising. Adults were the dominant group in general

when looking at how the three companies represented age in their advertising, but in contrast to

Sony, the percentage of adults appearing in Microsoft’s commercials made up 64% of all


characters, and adults appearing in Nintendo commercials made up just 41.9% of all characters.

Nintendo, as the previous number would suggest, was the most inclusive and diverse company in

terms of age, with every category present in their advertising, and the lowest category, older

adults, still making up 9.5% of the total population of characters observed.

Examining differences in racial, gender, and age representation over time. RQ2

asked to what extent are gender, racial, and age identities represented in advertisements for

consoles between 2003 and 2017. In the case of gender representation, men were on average

overrepresented versus women, making up anywhere between 60% to 74% of the total

population in Time Periods 1, 4, and 5. Of note, however, are Time Periods 2 (2006-2008) and 3

(2009-2011). From 2006 to 2008, the coded data featured 53.5% of men and 43.6% of women,

and from 2009 to 2011, the coded data included 57.8% men and 39.8% women. Though this

renaissance was short lived, it seems to represent a concentrated effort at gender diversity that

took place in industry marketing for about five years before representation of women again fell

off, never quite recovering. The most likely culprit for this difference in representation is due to

where these years sit in terms of console releases. From 2006 to 2011, The only home consoles

being advertised and sold were the Xbox 360, Nintendo Wii, and the PlayStation 3, Each of

which began sale around 2006 and were phased out in favor of newer consoles around 2012 and

2013.

Applying cultivation theory, we may conclude that women may feel that the industry

recognizes their presence but prefers to focus on men first. In addition, literature on cultivation

covering similar topics would indicate that those who are exposed frequently to these

commercials will likely conclude that women are either losing interest in video games or are


otherwise uninterested in video games in general. Of the relevant findings from this study, this

specific finding should be explored in further research.

When observing what the data show us regarding representations of age, there were a few

interesting findings from which we may draw further implications. For example, representation

of middle age individuals is split nearly evenly among Time Periods 1-3, before completely

falling off for Time Periods 4 and 5. Furthermore, we see a spike in the representation of nearly

all groups other than the dominant adult group being relatively equally represented, with

percentages ranging between 8.9% and 11.9% of the total representation, making Time Period 2

the most diverse Time Period observed. Outside of these observances, spikes and dips are

observed among each of the categories, while the adult group stays a consistent dominant

averaging between 60-76% of total time population of characters in any given Time Period.

Certainly, the message that this representation sends to consumers is that while anyone may have

fun playing these video games, they are actually meant for the young adult crowd, with any other

group being secondary.

The findings on age are consistent with the literature reviewed in preparation for this

study, where adult representation is prioritized over older adults and children (Williams, Martins,

Consalvo, & Ivory, 2009; Chess, Evans, & Baines, 2016). The Williams Martins, Consalvo, and

Ivory (2009) article uses this finding to point out that as gamers get older, and indeed as older

players start playing games seeing that the average age of gamers is steadily rising, these groups

are not seeing themselves represented. Further, Chess et al (2016) found that typical

representations of age present in the commercials they observed from 2013 were used in the

context of family members. This also happened to be the case in many of the commercials

observed in this project, where only a select few ads displayed older adults playing games on


their own without children playing with them, and even in these limited cases, these individuals

were often used as observational comedy implying people aged over 50 playing games is a wild

and humorous concept. These representations, according to cultivation theory can further such

unwelcoming stereotypes surrounding older players. Just as with cases of gender and racial

identity discussed earlier, this creates a common misconception that older individuals should not

be playing video games, and there is no place for them in the community at large.

Examining differences in racial, gender, and age representations by company over

time. RQ3 asked how Microsoft, Nintendo, and Sony differ in their representations of racial,

gender, and age identity over time from 2003 and 2017. Interestingly, though Sony seemed to be

the most diverse and inclusive for racial identity in the exploration of RQ1, data in this section

suggests that this is due to the consistency at which Sony included representations over the five

Time Periods, as no significance was determined in change or trend. Black representation in

relation to other groups steadily making up around 10% of the characters observed in each tie

period, spiking to 27.3% in Time Period 1 and 23.1% in Time Period 4. Sony was so consistent,

in fact, that no significance was found in their representations of age or gender over the five

Time Periods, though it was interesting to see that Sony rarely included non-adults in their

commercials.

Microsoft had some of the more interesting findings in the exploration of this research

question, especially when it came to gender. The significance found in RQ2 regarding the rise in

the representation of women versus men seems to be skewed by the Microsoft commercials

observed during that time. In Time Periods 2 and 3, representations of women outnumbered men,

which is the only case of a typically minority group overcoming representation of a majority


group in all of my observations in this study. This shift in demographics does not stay, however,

as subsequent Time Periods see an extremely sharp drop in representation of women. As

discussed earlier, the Xbox 360 was released in late 2005 and was phased out in favor of the

newer Xbox One in 2013. In short, this means that advertising from Microsoft in Time Periods 2

and 3 was focused on the marketing of the one console. The shifting in marketing from Xbox to

Xbox 360 to Xbox One may be the explanation in disparity in strategy, though it is interesting

that these shifts were not as evident in Sony’s advertising.

Another interesting finding from Microsoft’s data is the trend observed in racial

representation over time. Although relatively no groups outside of White are represented until

Time Period 5, we see instances of white representation dip consistently from period to period

until Period 5, where there were as many White individuals coded as there were Black

individuals, with Arab American and Latinx representation lagging shortly behind. The

implication that may be drawn from these data may be that Microsoft is making a more

concentrated effort to become more inclusive in their advertising since the release of their most

recent console, the Xbox One. this conclusion is drawn due to the fact that the release of the

console happened late in 2013 to low sales versus the PlayStation 4 (Gilbert, 2017), which could

have prompted the dramatic shift in marketing strategy seen between Time Periods 4 and 5.

Finally, Microsoft’s representations of age also saw significance in the difference over

time. Though Time Periods 1, 2, 4, and 5 see the adult group in the majority, with little

representation from other groups; in Time Period 3 adult representation drops to 17.6% of the

total population observed, being replaced with representations of adolescents and middle-aged

individuals. In addition, middle-aged individuals made up 22.9% of the population of characters

observed for Time Period 1. Though variances are observed in certain sections, there is no trend


towards diversity or inclusivity over time, leading to the conclusion that adults are the most

dominantly represented age group in Microsoft marketing.

Nintendo, much like Sony, had no significance determined in the representations of

gender or racial identity. However, significance was determined in the differences in

representations of age in Nintendo advertisements, lending insight to data observed on age over

time in the exploration of RQ 2. Nintendo emerged as the leaders of age diversity in the first

three Time Periods, with a reasonably even distribution of representation in Time Periods 1 and

3, with a huge spike in the representation for all groups observed in Time Period 2. The

aforementioned spike coincides with the release of the Wii console, which Nintendo did their

best to market towards all ages, making it the third bestselling home console of all time (Statista,

2017), and notably popular in senior homes across the United States (Conaway, 2009).

Interestingly, in Time Period 5, pre-adolescent individuals were equally represented to adult

individuals. The major implication that may be drawn from the variances observed in these data

is that though no linear trends are present over time, the variety in representation observed in the

different Time Periods seems to indicate that Nintendo values gamers of all age categories nearly

equally, while still relying on adults from time to time as a primary demographic.


CHAPTER VI: CONCLUSION

In this thesis project, racial, gender, and age representations in video game console

advertisements that aired between 2003 and 2017 were examined. Using cultivation theory as a

framework, this study has effectively answered its three research questions to reveal troubling

patterns in the underrepresentation of people of color, women, and non-adults. Though perhaps

the industry is not overall trending towards better diversity or inclusion, there were findings that

may lend to feelings of hopefulness that the industry may soon make their advertisements more

representative of its consumer base. In the following chapter, the apparent limitations of this

study are first discussed, before concluding with calls for future research on this topic.

Limitations

This study, though enlightening in many regards, is not without some key limitations.

The first limitation is the lack of a certifiably comprehensive archive of all video game

commercials online. Though the website Gamepressure seemed to be very comprehensive in its

cataloging of new commercials as they air on television and online, working backwards

highlighted the issue that care was not taken to archive and save every commercial before the

rise of cheap and easy video hosting online. As a result, commercials became increasingly sparse

when looking for commercials that aired between 2003 and 2008. Efforts were made to branch

out and find commercials hosted on various other sites such as YouTube, but the lack of an

archival or categorical format made it difficult to find commercials if one does not have a

specific title and made it difficult to verify date of initial air. This limitation resulted in missing

data from Microsoft in Time Period 1 and Time Period 2, where only four commercials were

found featuring human characters. One of those four commercials found also had to be removed

as it skewed the data collected in a way that was not representative of all other commercials


observed. Another major limitation would be the natural time constraints that come along with

doing this type of study as a master’s thesis. These time constraints limited me to a

representative sample of all commercials, have thesis had more time, the total population of

commercials could have been ideally coded to give a more comprehensive census of all

representation present in video game console commercials.

Future Research

Further research on the topic of representation in video game commercials building upon

the work started in this thesis. First, the data collected and analyzed in this thesis could be used

to inform critical and qualitative studies on the video game industry and its marketing strategies

to evaluate why such groups are marketed, why others are not present, and what relative success

from each company says about the impact of this marketing. Second, future research could

examine a wider time range of media message. Although this project tracks racial, gender, and

age representations over a 15-year period, additional scholarship could go further into the past by

examining video game console commercials over the past 30 years. Lastly, future scholarship

could benefit from this work being continued every three years. Continual examination on the

gaming industry’s efforts at diversity and inclusivity will continue to be salient as long as video

games remain a dominant form of media. Research such as this thesis will help to trace and

analyze how the industry shifts (or does not shift) to market towards a more diverse array of

consumers.


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APPENDIX A: CODE BOOK USED TO ANALYZE THE DATA

Category Codes Definition Exemplar

Character Role

Primary Those characters depicted as directly engaging with the game or product advertised, or are otherwise clearly framed as the gamer in the advertisement

Gamers

Secondary Those characters not depicted as directly engaging with the game or product advertised, or are otherwise depicted as an observer, friend, or antagonist of the primary character

Spectators, friends, antagonists

Perceived Race

Black, African, or African American

Persons who have phenotypical traits derived from heritage in Africa or certain Caribbean nations

Barack Obama, Jimi Hendrix, Oprah Winfrey, Michael Jordan, Nelson Mandela

White Persons who have phenotypical traits derived from heritage in Europe

John F. Kennedy, David Beckham, Taylor Swift, George Clooney

Latinx Persons who have phenotypical traits derived from heritage in Latin America or certain Caribbean nations

Carlos Santana, Sofia Vergara, Vicente Fox, George Lopez, Guillermo Del Toro


Native American or American Indian

Persons who have phenotypical traits derived from heritage in First Nation tribes across the Americas

Jim Thorpe, Russell Means, Sherman Alexie, Jay Silverheels, Dennis Banks

Arab or Arab American

Persons who have phenotypical traits derived from heritage in the Middle East

Sadiq Khan, Tony Shalhoub, Rima Fakih, Rami Malek, DJ Khaled

Asian and Pacific Islander

Persons who have phenotypical traits derived from heritage in East Asia, South Asian, Southeast Asian, Oceania, or Pacific Ocean islands

Chow Yun-fat, Jackie Chan, Shinzo Abe, Dwayne Johnson, Kumail Nanjiani, Aziz Ansari, Hideo Kojima, Lucy Liu

Other Persons who have phenotypical traits derived from heritage not listed above

Unable to Determine

This category pertains to those persons whose visual traits are ambiguous to a degree that they are unable to be placed in above categories

Perceived Gender

Man Persons who have phenotypical traits which are defined as predominantly masculine rather than feminine

Matthew Stafford, Calvin Johnson, Haloti Ngata, Henrik Zetterberg, Justin Verlander


Woman Persons who have phenotypical traits which are defined as predominantly feminine rather than masculine

Scarlett Johansson, Halle Berry, Salma Hayek, Rosario Dawson, Emma Stone

Trans Persons who have phenotypical traits which are defined as androgynous, or display traits indicative of a transition from masculine to feminine or feminine to masculine

Caitlyn Jenner, Laverne Cox, Chaz Bono, Alexis Arquette, Lana Wachowski, Lilly Wachowski, Chelsea Manning, Thomas Beattie

Unable to determine


Perceived Age

Pre-Adolescent

Persons who have phenotypical traits associated with childhood and early development, aged 12 and under

Mike Wheeler, Will Byers, Dustin Henderson, Lucas Sinclair, August Maturo

Adolescent Persons who have phenotypical traits associated with teenagers, aged 13 to 18

Jacob Sartorius, Chandler Riggs, Jaden Smith, Ariel Winter

Adult Persons who have phenotypical traits associated with adulthood, aged 19 to 34

Elle Fanning, Bella Thorne, Dakota Fanning, Odell Beckham Jr.


Jennifer Lawrence, Julio Jones, Antonio Brown, Le’veon Bell, Eddie Lacy, Adrian Peterson

Middle aged Persons who have phenotypical traits associated with middle age, aged 35 to 64

Chris Pratt, Bradley Cooper, Channing Tatum, Ryan Gosling, Ryan Reynolds

Nicole Kidman, Jennifer Aniston, Brad Pitt, Matthew Perry

Tom Cruise, Sharon Stone, Sheryl Crow, John Elway, Steve

Older Age Persons who have phenotypical traits associated with older adults, aged 65 and older

Mark Hamill, Samuel L. Jackson, Meryl Streep, Kurt Russell, Sigourney Weaver

Patrick Stewart, Harrison Ford, William Shatner, Clint Eastwood

Unable to Determine



APPENDIX B: CODING WORKSHEET

Is the character primary or secondary?

( ) Primary ( ) Secondary

What is the character’s perceived ethnicity?

( ) White ( ) Black or African American ( ) Native American or American Indian ( ) Hispanic or Latino ( ) Arab American ( ) Asian or Pacific Islander ( ) Other ( ) Unable to Determine

What is the character’s perceived gender?

( ) Man ( ) Woman ( ) Trans ( ) Unable to Determine

What is the character’s perceived age?

( ) Pre-Adolescent ( ) Adolescent ( ) Adult ( ) Middle Age ( ) Older Age ( ) Unable to Determine

diversity and inclusivity in video game advertisements

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