The Social Life of  Second Life An analysis of the Social Networks of a virtual world Aleks Krotoski Networks Network, 27 ...
Research Questions <ul><li>What are the underlying social psychological phenomena which contribute to the effectiveness of...
The context
 
 
How can the interactions in cyberspace be  meaningful  ? In traditional definitions of “community”, there’d be no such thi...
The Importance of Being  Pseudononymous <ul><li>Anonymity </li></ul><ul><ul><li>Users demonstrate enhanced self-awareness ...
The Importance of Being Pseudononymous <ul><li>Most psychological internet research suggests that anonymity increases  dei...
The Importance of Being Pseudononymous <ul><li>However, most of the online influence research has been conducted in  exper...
Three studies <ul><li>Study 1 (completed June 2006) </li></ul><ul><ul><li>To assess the best sociometric criteria for coll...
Three Studies <ul><li>Study 3 (data collection May 2007) </li></ul><ul><ul><li>To measure the SL network at the individual...
Study 1: Method <ul><li>Online survey </li></ul><ul><ul><li>Demographics  </li></ul></ul><ul><ul><li>SN name generator (Ca...
Study 1: Results <ul><li>N (respondents) = 33  </li></ul><ul><li>N (actors) = 650 </li></ul><ul><li>N (arcs) = 1734 </li><...
 
<ul><li>SNC scale offers a more robust measure of the effect of the social network on influence, by controlling for potent...
Picking apart the “communication”  network closeness assumption <ul><li>But what does it mean –  psychologically  - if som...
Results: Single explanatory variable (General Communication) <ul><li>The predictive power of the estimate of the value of ...
Single explanatory variable:  General Trust & SNC categories <ul><li>Effect of interpersonal closeness on mode of communic...
Results: Multiple explanatory  variables (General Trust) <ul><li>Greatest improvement to the fit of a model occurs when of...
Discussion (Study 1) <ul><li>Consistent with Latan é ’s research  </li></ul><ul><ul><li>people who are in greater communic...
Study 2: Method <ul><li>Online survey </li></ul><ul><ul><li>Demographics </li></ul></ul><ul><ul><li>SN name generator (Fri...
Study 2: Results <ul><li>N (respondents) = 750 </li></ul><ul><li>N (actors) = 6767 </li></ul><ul><li>N (arcs) = 9595 </li>...
Density = 0.082
Position and SP 6653.37 0.534 (0.017) 0.190 (0.022) 0.803 (0.026) Prototypicality (N=2685) 0.483 (0.016) 0.530 (0.018) 0.5...
Opinion leaders <ul><li>More likely to be sources of information because have access to broader info pool </li></ul><ul><l...
Opinion Leader demographics <ul><li>Older than average </li></ul><ul><li>More likely to be female than average </li></ul><...
 
 
 
Limitations <ul><li>Self-reported experiences of 750 actors (ego-centric) </li></ul><ul><li>Partial network </li></ul><ul>...
Study 3 Adoption data for new technological innovation (Voice)
Voice in Second Life <ul><li>Contentious issue </li></ul><ul><li>Relevant to entire virtual world </li></ul><ul><ul><li>Wh...
<ul><li>Descriptive </li></ul><ul><li>Community Building and Protection </li></ul>
Questions? Aleks Krotoski [email_address]
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The Social Life of Second Life: An analysis of the networks of a virtual world

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for the Networks Network at University of Surrey, 27 April 2007

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    Sharika
    http://winkhealth.com http://financewink.com
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  • The Social Life of Second Life: An analysis of the networks of a virtual world

    1. 1. The Social Life of Second Life An analysis of the Social Networks of a virtual world Aleks Krotoski Networks Network, 27 April 2007
    2. 2. Research Questions <ul><li>What are the underlying social psychological phenomena which contribute to the effectiveness of a method like SNA? </li></ul><ul><li>What do network definitions mean in social psychological terms? </li></ul><ul><li>What social psychological knowledge might contribute to the greater predictive quality of the method? </li></ul><ul><li>What are the relative contributions of each on a measure of social influence? </li></ul>
    3. 3. The context
    4. 6. How can the interactions in cyberspace be meaningful ? In traditional definitions of “community”, there’d be no such thing in cyberspace How can you develop meaningful relationships with people you’ve never met ?
    5. 7. The Importance of Being Pseudononymous <ul><li>Anonymity </li></ul><ul><ul><li>Users demonstrate enhanced self-awareness when online, and elaborate on the CONTENT rather than peripheral persuasive cues </li></ul></ul><ul><ul><li>Immersion as a mediator </li></ul></ul><ul><ul><ul><li>people are more likely to focus on peripheral cues, like perceived trustworthiness, likeability, credibility and expertise of a source in an environment like Second Life (e.g., Blascovich & Yee, 2005) </li></ul></ul></ul>
    6. 8. The Importance of Being Pseudononymous <ul><li>Most psychological internet research suggests that anonymity increases deindividuating behaviour </li></ul><ul><ul><li>From Zimbardo’s nuns to strangers on a train </li></ul></ul><ul><ul><li>Online, conformity and compliance behaviours have been theorised to be a result of similar processes (e.g., SIDE) </li></ul></ul><ul><ul><li>As have less agreeable behaviours (e.g., flaming, griefing) </li></ul></ul>
    7. 9. The Importance of Being Pseudononymous <ul><li>However, most of the online influence research has been conducted in experimental situations , with simulated e-groups </li></ul><ul><li>What about the norms ? </li></ul><ul><ul><li>Hierarchies, rules, practices, rituals </li></ul></ul><ul><li>What about online identity ? </li></ul>
    8. 10. Three studies <ul><li>Study 1 (completed June 2006) </li></ul><ul><ul><li>To assess the best sociometric criteria for collecting relational data in Second Life </li></ul></ul><ul><ul><li>To assess the social psychological definition of the social network concepts “closeness” and “distance” </li></ul></ul><ul><li>Study 2 (completed April 2007) </li></ul><ul><ul><li>To extend Study 1 and to replicate the findings on a larger scale </li></ul></ul><ul><ul><li>To assess the individual contributions of social network and social psychological factors on a measure of social influence </li></ul></ul>
    9. 11. Three Studies <ul><li>Study 3 (data collection May 2007) </li></ul><ul><ul><li>To measure the SL network at the individual (Friends) and group (Groups) level </li></ul></ul><ul><ul><li>To follow the diffusion of an innovation through SL at the individual and group level </li></ul></ul><ul><ul><li>To assess the effect central avatars have on diffusion </li></ul></ul><ul><ul><li>To ascertain any mediating effects group membership has on adoption </li></ul></ul>
    10. 12. Study 1: Method <ul><li>Online survey </li></ul><ul><ul><li>Demographics </li></ul></ul><ul><ul><li>SN name generator (Calling Cards) </li></ul></ul><ul><ul><li>SNTrust and SNCommunication scales </li></ul></ul><ul><ul><li>Social Psychological items </li></ul></ul>
    11. 13. Study 1: Results <ul><li>N (respondents) = 33 </li></ul><ul><li>N (actors) = 650 </li></ul><ul><li>N (arcs) = 1734 </li></ul><ul><li>Average neighbours: 2.32 (SD=11.10; min = 1, max = 331) </li></ul>
    12. 15. <ul><li>SNC scale offers a more robust measure of the effect of the social network on influence, by controlling for potential confluence with the social psychological measures. </li></ul><ul><li>The Social Network Communication Scale is a more discrete measure of a “social network” in this environment, whilst retaining reliable network measures </li></ul><ul><li>Instances of communication are the only way for Residents to develop interpersonal trust online </li></ul>
    13. 16. Picking apart the “communication” network closeness assumption <ul><li>But what does it mean – psychologically - if someone in Second Life is rated “close” or “distant” with communication criteria? </li></ul><ul><li>Multi-Level Modelling (models) </li></ul>
    14. 17. Results: Single explanatory variable (General Communication) <ul><li>The predictive power of the estimate of the value of this measure of General Trust is positively enhanced when we know how often two people communicate in general. </li></ul>*N=538; **N=539; σ 2 e : variance accounted for between avatars; T p<0.000, df=2 0.347 (0.023) 0.408 (0.027) 0.408 (0.027) 0.531 (0.035) 0.543 (0.035) σ 2 e 1086.919 T (1141.021) 0.271 (0.055) 0.035 (0.125) Domain-Specific Trust 1114.31 T (1345.777) 0.645 (0.064) -0.135 (0.098) General Trust 987.966 T (1132.416) 0.399 (0.064) -0.098 (0.118) Social Comparison 1272.354 T (1404.954) 0.519 (0.071) -0.093 (0.102) Credibility 1292.354 T (1335.299) 0.305 (0.066) 0.026 (0.101) Prototypicality Loglikelihood (fixed model LL) β (Std. Error) β 0 (Std. Error) y
    15. 18. Single explanatory variable: General Trust & SNC categories <ul><li>Effect of interpersonal closeness on mode of communication (e.g., Garton et al , 1997) </li></ul><ul><li>Offline communication contributes the most to the estimate of General Trust. Online public communication contributes the least. </li></ul>N=539; σ 2 e : variance accounted for between avatars; T p<0.000, df=2 0.427 (0.028) 0.407 (0.027) 0.476 (0.031) σ 2 e 1159.681 T (1345.777) 0.459 (0.047) 0.070 (0.090) Offline Communication 1115.396 T (1345.777) 0.442 (0.062) 0.070 (0.094) Online Private Communication 1124.182 T (1345.777) 0.370 (0.052) 0.085 (0.093) Online Public Communication Loglikelihood (fixed model LL) β (Std. Error) β 0 (Std. Error) Explanatory Variable
    16. 19. Results: Multiple explanatory variables (General Trust) <ul><li>Greatest improvement to the fit of a model occurs when offline communication scores are added to the single-variable public communication model </li></ul><ul><li>Adding online private communication to the online public communication model renders the weight of online public communication insignificant, so this model is rejected. </li></ul>Loglikelihood (fixed model LL) σ 2 e β2 (Std. Error) β1 (Std. Error) β 0 (Std. Error) Explanatory Variable 0.328 (0.046) 0.291 (0.051) 0.375 (0.074) N=539; σ 2 e : variance accounted for between avatars; T p<0.000, df=3; *model rejected on basis of ill-fit 0.314 (0.021) 0.332 (0.022) 0.394 (0.026) 1038.486 T (1115.396) 0.345 (0.057) 0.052 (0.087) Online private and offline communication 1057.941 T (1224.182) 0.399 (0.051) 0.059 (0.085) Online public + offline communication 1144.879 T (1224.182) 0.104 (0.057) 0.065 (0.121) Online public + online private communication
    17. 20. Discussion (Study 1) <ul><li>Consistent with Latan é ’s research </li></ul><ul><ul><li>people who are in greater communication have greater social impact </li></ul></ul><ul><li>Provides empirical evidence for Garton et al (1997), Correll (1995). </li></ul><ul><li>What about position? What about structure? </li></ul>
    18. 21. Study 2: Method <ul><li>Online survey </li></ul><ul><ul><li>Demographics </li></ul></ul><ul><ul><li>SN name generator (Friends) </li></ul></ul><ul><ul><li>SNCommunication scale </li></ul></ul><ul><ul><li>Social Psychological items </li></ul></ul><ul><ul><li>Measure A to assess perceived trust towards central and peripheral avatars about general risk behaviours in Second Life . </li></ul></ul><ul><ul><li>Measure B which measures baseline attitudes about taking part in Second Life -specific risk activity. </li></ul></ul>
    19. 22. Study 2: Results <ul><li>N (respondents) = 750 </li></ul><ul><li>N (actors) = 6767 </li></ul><ul><li>N (arcs) = 9595 </li></ul><ul><li>Average neighbours (in-degree) = 1.42 (SD= 1.09; min = 0, max = 17) </li></ul><ul><li>Components </li></ul><ul><ul><li>62 strong components > 2 </li></ul></ul><ul><ul><li>7 strong components > 5 </li></ul></ul><ul><li>Top 46 in-degree (8-17) </li></ul>
    20. 23. Density = 0.082
    21. 24. Position and SP 6653.37 0.534 (0.017) 0.190 (0.022) 0.803 (0.026) Prototypicality (N=2685) 0.483 (0.016) 0.530 (0.018) 0.532 (0.018) 0.531 (0.018) 0.420 (0.013) σ 2 e 6400.24 0.312 (0.020) 0.797 (0.026) Social Comparison (N=2685) 6460.3 0.240 (0.021) 0.805 (0.025) Trust about privacy (N=2649) 6510.62 0.215 (0.021) 0.809 (0.026) Trust about sex (N=2649) 6560.19 0.191 (0.021) 0.802 (0.026) Trust about business (N=2651) 6162.35 0.432 (0.020) 0.773 (0.023) Social network trust (N=2786) Loglikelihood (fixed model LL) β (Std. Error) β 0 (Std. Error) y
    22. 25. Opinion leaders <ul><li>More likely to be sources of information because have access to broader info pool </li></ul><ul><li>Their adoption is likely to spread through local networks because </li></ul><ul><ul><li>Trusted </li></ul></ul><ul><ul><li>Viewed as prototypical </li></ul></ul><ul><ul><li>Sources of others’ social comparison </li></ul></ul>
    23. 26. Opinion Leader demographics <ul><li>Older than average </li></ul><ul><li>More likely to be female than average </li></ul><ul><li>Greater than average time spent in community </li></ul><ul><li>Greater number of hours spent in SL per week </li></ul><ul><li>Concerned with anti-social behaviour </li></ul>
    24. 30. Limitations <ul><li>Self-reported experiences of 750 actors (ego-centric) </li></ul><ul><li>Partial network </li></ul><ul><li>Analytic strategy emphasises greater connectivity </li></ul>
    25. 31. Study 3 Adoption data for new technological innovation (Voice)
    26. 32. Voice in Second Life <ul><li>Contentious issue </li></ul><ul><li>Relevant to entire virtual world </li></ul><ul><ul><li>Who uses? </li></ul></ul><ul><ul><li>How long? </li></ul></ul><ul><ul><li>Where? </li></ul></ul><ul><ul><li>What type? </li></ul></ul>
    27. 33. <ul><li>Descriptive </li></ul><ul><li>Community Building and Protection </li></ul>
    28. 34. Questions? Aleks Krotoski [email_address]

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