the social media impact on the networked world - city...
TRANSCRIPT
Research Ideas & Projects:
The Social Media Impact on the Networked World
Dr. Bu Zhong College of Communications
Pennsylvania State University
February 17, 2014 City University of Hong Kong
Dr. Bu Zhong
Current • Visiting Prof., HKBU; Assoc. Prof., Penn State • Vice President, CCA; President, MC&S of AEJMC • AEJMC Standing Committee on Research Teaching • Social Media for Social Change • Social Media Research • Social Media Marketing Research • Impact of social media and mobile technology • Information flow in networked communities
Today’s Content
• SM Research Ideas & Projects – Two Studies on Social Media – Two Ongoing Projects – Computer-aided Content Analysis
• An Interactive Lecture – If it’s a small question, ask it any time. – If it is big, hold until Q&A.
Which Country?
What Does This Mean? “The World Is Changed.”
Our Contribution
Communication researchers are uniquely trained to analyze
human interaction with others and information
in a carefully and nuanced ways, in terms of both causes and
consequences.
Social Media – A Global Phenomenon
Go Mobile in Africa
Pay friends via your phone?
Mobile Banking in Kenya Mobile phone – Pay friends, bills, buy basics in Kenya
Research Ideas & Projects involving social media
Social Media
Human Interaction
Interaction with information
Interaction with People
Some Links Being Built …
• SM use and personality – Social media use and shallow thinking (Zhong,
Hardin & Sun, 2011)
– Social media use and anxiety regulation (Hanley, Howard, Zhong, & Soto, in press)
– Power users’ disposition towards to mobile technology (Zhong, 2013)
Study 1
SM Use & NFC
• Need for Cognition (NFC) is an important
personality attribute that moderates computer-mediated communication.
About NFC
• Low NFC people do not enjoy effortful thinking but thinking is fun to the high NFC (Kaynar & Amichai-Hamburger, 2008).
• High NFC people has a high motivation to think and seek knowledge (Petty & Cacioppo, 1986), and process information more thoroughly (Verplanken, 1993; Verplanken et al., 1992).
Findings
Findings
Discussion
• High NFC people tended to use SNS less often • High NFC people less likely to add anyone to
their SNS accounts than low NFC individuals. • Effortful thinking associated with SNS use.
Study 2: Power Users
Power Users – A New Concept?
• Power Users – Those who use mobile media technology
thoroughly, innovatively and productively.
• Previous studies:
– Innovative users (Rogers, 2003) – Heavy users and light users (Appel, 2012)
This Research
• Power users’ disposition toward MMD. – Personality traits: NFC, ICT innovativeness – Media multitasking – Traditional media use
• The findings help understand … – adoption of mobile tech – diffusion of mobile tech
A Theoretical Framework
• The “Diffusion of Innovation” theory (Rogers, 1995) – It studies how people adopt a tech innovation
1. Innovators 2. Early Adopters
3. Early Majority
4. Late Majority
5. The Laggards
Innovators (Rogers, 1995)
• Very early adopters • Active info-seekers about
new ideas • Cope with higher levels of
tech uncertainty • Embrace innovations
Power Users (Zhong, 2013)
• Not always early adopters • Exploit MMD to the fullest
extent (Schlosser, 2000) • Intense interest in new MMD • Read, write MMD reviews • A driving force behind new
versions of MMDs • Not only embrace innovations
but also experts in using the technology
The Variables
• Scale of Power Use – 1) enjoy using MMD; – 2) use most MMD features productively; – 3) love to learn new MMD features; – 4) always need help in using MMD (reverse coded) – 5) too complicated to use MMD (reverse coded) – 6) take long time learning MMD (reverse coded)
• Personality traits – Need for Cognition (NFC) – ICT innovativeness
Findings
power use of MMDs
Testing Hypotheses
• H1. High NFC individuals power users. – Not confirmed
• H2. High in ICT innovativeness more time on MMDs – Confirmed
• H3. People high in ICT innovativeness power users – Confirmed
• H4. Multitaskers power users – Confirmed
Conclusion
• This study proposes the new construct of power user and presents a first look at their characteristics toward MMDs at their early adoption stage, a critical time for “examining the relationship between engagement and ICT” (Cazares, 2010, p. 1005).
Ongoing Research Projects with Practical Implication
Research in Progress 1
Information flow empowers vegetable farmers/vendors in Chengdu, China
Vegetable Markets in Chengdu Traditional Model Our Model (200 markets) (30 markets)
A Traditional Model
The Yiming Model
Model of Price Prediction
Week 1 Sales Data
Week 2 Sales Data
Week 3 Sales Data
Model
Predicted Price
Actual Price
Predicted Price for Week 4
Data Used in the Model • Sales data in 30 veg
markets – prices, amount, time/date
• Wholesale prices, weather data, supply data, transportation, etc.
Big Data Enhance the Model
Model of Price
Prediction
W1-5 Price
W6-10 Price
W11-15 Price
Benefits from the Model • Lower veg. price (15% lower on average, some 70%) • More profits for farmers/veg companies • Prices predicable, stabilized. • Food security (bar codes make veg. source
traceable), branding, insurance • The model may be used in other cities.
Former Premier Wen Visits Yiming Vegetable Market
• More people use social media to keep abreast of personal health and well-being issues. – Professional web portals, e.g., WebMD.com and
MedicineNet.com – Medical forums, e.g., DiabetesForum.com,
IBSGroup.org for IBS
• Better diagnosis of IBS • Improved relations between IBS patients and doctors • Personalized treatment of IBS • Enhance life quality among IBS patients
Computer-Aided Content Analysis • http://www.wjh.harvard.edu/~inquirer/
The CACA Advantages
1. The stability and comparability of coding rules lead to more accuracy of the research findings. 2. Perfect coder reliability in applying the rules to texts with no individual differences, human errors, and fatigue factors 3. It can process huge quantities of text data with exceptional speed.
The General Inquirer
• The GI was developed by Philip J. Stone at MIT in the 1960s (Oglivie, Stone, & Kelly, 1982)
• One of the earliest and most widely used tools for computer-aided content analysis.
• The GI results show high internal and external validity.
• It can be used on any operating systems with a Java Virtual Machine.
How the GI Works?
• It relies on the classification system, also called the ‘‘dictionary.’’
• The GI employs the Harvard Psychosociological Dictionary, i.e., Harvard-IV-4 TagNeg (H4N).
• The H4N is also featured in many other CACA systems, including Protan, TextQuest, and WordStat.
A Big Advantage • The GI analyzes different meanings of a word in contexts. • The GI’s two-step process:
– First it identifies homographs—ambiguous words with different meanings in a context.
– Second it uses preprogrammed disambiguation rules to clarify the meaning in the text (Pennebaker et al., 2003).
– e.g., ‘‘That’s a bad boy.’’ The GI first identifies the word ‘‘bad’’ as an ambiguous word, then code it as positive or negative after analyzing the context.
• There are 182 predefined word categories in the GI dictionary.
• Positive and negative word categories are the latest and largest, reaching 10,827 words (Loughran & McDonald, 2011).
MXiknFBaZ
The GI Output
