Interpersonal Relationships in Group Interaction in CSCW

Environments

Yang Cao, Golha Sharifi,

Yamini Upadrashta, Julita Vassileva

University of Saskatchewan,

Canada

Outline

• Introduction• Game design• Rules• Experiments• Results• Conclusions• Future work• Link to workshop questions

Introduction• Social factors in multi-user environments

– user motivation, attitudes to others, personal relationships and social networks

– emerging, self-organizing social dynamics– how environment mediates is important

• We are interested to find out• how people develop and change their attitudes of liking or

disliking other people • how the motivation influences attitude change• how the design of the environment influences attitude change and

the emergent social fabric of the group

• Tool: a new multi-user web-based computer game

The game

Game design (1/2)

• Goal:• To send a packet to a given other player with minimum loss.

• Game Description:• A player chooses a destination player and sends to him/her a

signed packet • It can send it only by passing it to one of the other players. • The selected player can (depending on whether s/he dislikes

or likes the originator of the packet). • destroy it completely • take away a part of the packet and pass it to another player• leave it untouched and pass it to another player

Game design (2/2)

• This continues until the packet reaches the destination or is destroyed.

• After each round the player can : • see if his/her packet has arrived entirely or partially

(proportion of 100).

• see a system generated rough representation of the attitudes of other players towards him/her (system model)

• change his/her attitudes to the other players.

Animation

Sender (A)

Destination (D)

Send this to D

(B)

(C)

I like B more than C, so I send

it through B

This has to go to D

I like A, so I won’t destroy her packet and I Don’t dislike

D so I send the packet to D

The packet reach the

destination(End of round)

Scenario 1:I don’t like A, so I will

destroy her packet.(End of round)

Scenario 2:I like A, so I won’t

destroy her packet and I like D more than C, so I send the packet to D

Scenario 3:I like A, so I won’t destroy

her packet but I like C more than D, so I will send the packet

to C

This has to go to D

The packet reach the

destination(End of round)

“A” sends a packet to destination “D”

Implementation

• Web-based (Apache Tomcat)

• Multi-Agent Architecture (FIPA)

Rules (1/3)

• A Personal Agent (PA) represents each player in the game

• The PA maintains a list of attitudes

{a1,…, ak} of the player towards the other k players, ai {1,2,3,4,5},where 1 means "dislike" and 5 means "like"

• PA sents the packet to the agent of the most liked player M | aM = maxi {a1, a2, …, ak}

Rules (2/3)

• The PA cannot send its packet to an agent that is strongly disliked by the user (ai =1)

• The PA of the player who originate the packet cannot send its packet directly to the destination

• If the player dislikes strongly the originator R of the package (aR = 1), the PA will destroy the packet and

the packet will not be passed further.– Otherwise, the PA takes away n parts of the package

where n = 5 – aR and aR {2,3,4,5}

Rules (3/3)• The round finishes when the packet reaches the

destination player or is destroyed. • The player that has accummulated a highest score of

passed packages wins the game.

• The PAs do not reveal the attitudes of their users to either other agents or to the system.

• Players can view their own attitudes towards the others at any time (player model).

• At the end of the round, each player can see the system model, which is computed by observing the passing of the package.

Using the game as a tool to study attitude formation

• The initial attitude-setting in a group

• How significant is the impact of individuality in attitude change

• The impact of different system feedback and visualization

• The impact of different user motivations

Hypotheses

• Individuals react differently, but consistently to success and failure when changing their attitudes to the other people involved in the situation;

• People reciprocate the attitudes of other people, when they become aware of them;

• The feedback about other people’s attitudes is given plays a role in the way people reciprocate and in the dynamics of the attitudes.

Two experiments with 2 versions

Text feedback version• 6 participants played

50 rounds• Questionnaire in the

end

Emoticon version• 7 participants played

40 rounds

45 minutes, 5-6 players at any given timePlayers had different gender, age, ethnic background (ignored)Players did not know who is who (aliases used in the game). The players were given a general introduction about the basic rules.

Results: how people choose initial attitudes to another player?

Average level of intial liking

0

5

10

15

20

25

30

35

40

1 2 3 4 5

textual feedback

emoticon feedback

Level of liking

% participants

Results: dynamics of attitude changeDistribution of attitude changes

0

10

20

30

40

50

60

70

80

drastic radical gradual const

Type of change

%

textual feedback version

emoticon feedback

Examples of attitude evolution

Daisy's Player Model Evolved with the Result of the Game

0

1

2

3

4

5

6

Initial-t0 Success-t2

Failure-t4 Partial_98-t6

Partial_99-t8

Partial_99-t10

Partial_99-t12

Partial_96-t14

Failure-t16

Time

Lik

e/d

islik

e

Goofy

Mickey

Pooh

Minnie

Donald

Pluto

Another example of evolution

Goofy's Player Model Evolved with the Result of the Game

0

1

2

3

4

5

6

Initial-t0 Partia_96-t1 Partial_99-t2 Failure_n-t3 Partial_98-t4 Failure-t5 Success-t6

Time

Like

/Dis

like

Daisy

Pooh

Mickey

Pluto

Minnie

Donald

Typical reactions

• Drastically reducing level of liking as a result of failure / partial failure in a game-round– Frequent for particular players– Targeted towards one most liked player– Targeted towards all most liked players

More typical reactions• Reciprocation

– Changing ones own attitude to another player to match the attitude of the other player – Comparing the mutual liking evolution curves for pairs of users pattern of delayed

reciprocity– Example – Pronounced difference between the two versions

• An average of 43.7% (median 50%) reciprocating changes across the players in the text feedback version and

• An average of 77% (median 73%) of reciprocating changes in the emoticon version.

Discussion

• Individuals react differently, but consistently to success and failure when changing their attitudes to the other people involved in the situation;

• People reciprocate the attitudes of other people, when they become aware of them;

• The way feedback about other people’s attitudes is given plays a role in the way people reciprocate and in the dynamics of the attitudes.

Conclusions

• Multi-player games offer a tool for studying the social dynamics of a group

• Individuality plays a significant role– It is possible to define typical reactions

• More work needs to be done to generate constructive results that can guide system design

How the paper addresses the WS questions:

1: Taxonomy of Circumstances Requiring Affective and Attitude User Modeling - in multi-user virtual environments, collaborative or not - the social experience is the determining factor for success2: Existing methods of Constructing Affective/Attitude User Models - modelling relationships / attitudes among users3: Validation and Evaluation - through the use of social (multi-player) games 4: Guidelines for model use - adapting the feedback and visualization

Future work

• The impact of the user motivation for participation (e.g. Win the game vs. Play the game) will be investigated

• Experiments with more participants by opening the game to players on the web

• To ease data analysis, synchronous rounds will be used

• To pinpoint the reason for changing attitude, user interviews and video observations, think aloud protocols will be used

• The role of the amount and the presentation of feedback information on the attitude formation of the user will be investigated further

Interpersonal Attitudes

Not necessarily reciprocal

So, each relationship is subjective, uni-directional

Player Model & System Model (textual feedback version)

Player Model & System Model (animated emoticon version)

Reciprocation exampleComparing Morteza and Abraham

0

1

2

3

4

5

6

Time

Lik

e/D

islik

e

Morteza vs . Abraham

Abraham vs . Morteza

Comparing Goofy and Mickey

0

1

2

3

4

5

6

0 305930 456717 880807 1037852 1194908 1489622 1607732

Time (ms)

Lik

e/D

isli

ke

Goofy Vs. Mickey

Mickey Vs. Goofy

Text feedback version

Emoticon Feedbackversion