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for the Networks Network at University of Surrey, 27 April 2007
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The Social Life of Second Life
An analysis of the Social Networks of a virtual world
Aleks KrotoskiNetworks Network, 27 April 2007
Research Questions
• What are the underlying social psychological phenomena which contribute to the effectiveness of a method like SNA?
• What do network definitions mean in social psychological terms?
• What social psychological knowledge might contribute to the greater predictive quality of the method?
• What are the relative contributions of each on a measure of social influence?
The context
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?
The Importance of Being Pseudononymous
• Anonymity– Users demonstrate enhanced self-
awareness when online, and elaborate on the CONTENT rather than peripheral persuasive cues
– Immersion as a mediator• 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)
The Importance of Being Pseudononymous
• Most psychological internet research suggests that anonymity increases deindividuating behaviour– From Zimbardo’s nuns to strangers on a
train– Online, conformity and compliance
behaviours have been theorised to be a result of similar processes (e.g., SIDE)
– As have less agreeable behaviours (e.g., flaming, griefing)
The Importance of Being Pseudononymous
• However, most of the online influence research has been conducted in experimental situations, with simulated e-groups
• What about the norms?– Hierarchies, rules,
practices, rituals
• What about online identity?
Three studies
1. Study 1 (completed June 2006)1. To assess the best sociometric criteria for
collecting relational data in Second Life2. To assess the social psychological definition
of the social network concepts “closeness” and “distance”
2. Study 2 (completed April 2007)1. To extend Study 1 and to replicate the
findings on a larger scale2. To assess the individual contributions of
social network and social psychological factors on a measure of social influence
Three Studies
3. Study 3 (data collection May 2007)1. To measure the SL network at the individual
(Friends) and group (Groups) level2. To follow the diffusion of an innovation
through SL at the individual and group level3. To assess the effect central avatars have on
diffusion4. To ascertain any mediating effects group
membership has on adoption
Study 1: Method
• Online survey– Demographics – SN name generator (Calling Cards)– SNTrust and SNCommunication scales– Social Psychological items
Study 1: Results
• N (respondents) = 33 • N (actors) = 650• N (arcs) = 1734• Average neighbours: 2.32
(SD=11.10; min = 1, max = 331)
• 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.
• The Social Network Communication Scale is a more discrete measure of a “social network” in this environment, whilst retaining reliable network measures
• Instances of communication are the only way for Residents to develop interpersonal trust online
Picking apart the “communication” network
closeness assumption
• But what does it mean – psychologically - if someone in Second Life is rated “close” or “distant” with communication criteria?
• Multi-Level Modelling (models)
Results: Single explanatory variable (General Communication)
y β0 (Std. Error)
β (Std. Error)
σ2e
Loglikelihood (fixed model LL)
Prototypicality 0.026 (0.101)
0.305 (0.066)
0.543 (0.035)
1292.354T (1335.299)
Credibility -0.093 (0.102)
0.519 (0.071)
0.531 (0.035)
1272.354T
(1404.954)
Social Comparison -0.098 (0.118)
0.399 (0.064)
0.408 (0.027)
987.966T
(1132.416)
General Trust -0.135 (0.098)
0.645 (0.064)
0.408 (0.027)
1114.31T
(1345.777)
Domain-Specific Trust
0.035 (0.125)
0.271 (0.055)
0.347 (0.023)
1086.919T
(1141.021)
*N=538; **N=539; σ2e: variance accounted for between avatars; Tp<0.000, df=2
• 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.
Single explanatory variable: General Trust & SNC
categoriesExplanatory Variable
β0 (Std. Error)
β (Std. Error)
σ2e Loglikelihood
(fixed model LL)
Online Public Communication
0.085 (0.093)
0.370 (0.052)
0.476 (0.031)
1124.182T
(1345.777)
Online Private Communication
0.070 (0.094)
0.442 (0.062)
0.407 (0.027)
1115.396T
(1345.777)
Offline Communication
0.070 (0.090)
0.459 (0.047)
0.427 (0.028)
1159.681T
(1345.777)N=539; σ2
e: variance accounted for between avatars; Tp<0.000, df=2
• Effect of interpersonal closeness on mode of communication (e.g., Garton et al, 1997)
• Offline communication contributes the most to the estimate of General Trust. Online public communication contributes the least.
Results: Multiple explanatory variables (General Trust)
Explanatory Variable β0 (Std. Error)
β1 (Std. Error)
β2 (Std. Error)
σ2e Loglikelihood
(fixed model LL)
Online public + online private communication
0.065 (0.121)
0.104 (0.057)
0.375 (0.074)
0.394 (0.026)
1144.879T
(1224.182)
Online public + offline communication
0.059 (0.085)
0.399 (0.051)
0.291 (0.051)
0.332 (0.022)
1057.941T
(1224.182)
Online private and offline communication
0.052 (0.087)
0.345 (0.057)
0.328 (0.046)
0.314 (0.021)
1038.486T
(1115.396)
N=539; σ2e: variance accounted for between avatars; Tp<0.000, df=3; *model rejected on basis of ill-fit
• Greatest improvement to the fit of a model occurs when offline communication scores are added to the single-variable public communication model
• Adding online private communication to the online public communication model renders the weight of online public communication insignificant, so this model is rejected.
Discussion (Study 1)
• Consistent with Latané’s research – people who are in greater
communication have greater social impact
• Provides empirical evidence for Garton et al (1997), Correll (1995).
• What about position? What about structure?
Study 2: Method
• Online survey– Demographics– SN name generator (Friends)– SNCommunication scale– Social Psychological items– Measure A to assess perceived trust
towards central and peripheral avatars about general risk behaviours in Second Life.
– Measure B which measures baseline attitudes about taking part in Second Life-specific risk activity.
Study 2: Results
• N (respondents) = 750• N (actors) = 6767• N (arcs) = 9595• Average neighbours (in-degree) = 1.42
(SD= 1.09; min = 0, max = 17)• Components
– 62 strong components > 2– 7 strong components > 5
• Top 46 in-degree (8-17)
Density = 0.082
Position and SPy β0 (Std.
Error)β (Std. Error)
σ2e
Loglikelihood (fixed model LL)
Social network trust (N=2786)
0.773 (0.023)
0.432 (0.020)
0.420 (0.013)
6162.35
Trust about business (N=2651)
0.802 (0.026)
0.191 (0.021)
0.531 (0.018)
6560.19
Trust about sex (N=2649) 0.809 (0.026)
0.215 (0.021)
0.532 (0.018)
6510.62
Trust about privacy (N=2649)
0.805 (0.025)
0.240 (0.021)
0.530 (0.018)
6460.3
Social Comparison (N=2685)
0.797 (0.026)
0.312 (0.020)
0.483 (0.016)
6400.24
Prototypicality (N=2685) 0.803 (0.026)
0.190 (0.022)
0.534 (0.017)
6653.37
Opinion leaders
• More likely to be sources of information because have access to broader info pool
• Their adoption is likely to spread through local networks because– Trusted– Viewed as prototypical– Sources of others’ social comparison
Opinion Leader demographics
• Older than average• More likely to be female than
average• Greater than average time spent in
community• Greater number of hours spent in SL
per week• Concerned with anti-social behaviour
Limitations
• Self-reported experiences of 750 actors (ego-centric)
• Partial network• Analytic strategy emphasises greater
connectivity
Study 3
Adoption data for new technological innovation
(Voice)
Voice in Second Life
• Contentious issue• Relevant to entire virtual world
– Who uses?– How long?– Where?– What type?
• Descriptive
• Community Building and Protection
