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Social Networks in Virtual Worlds

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Aleks Krotoski

presented 22 March 2007 at Massively Multi-Learner, The Higher Education Academy

Tecnologia
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Social Networks in virtual worlds Aleks Krotoski University of Surrey
Overview ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
But before we get ahead of ourselves… ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
So how can the interactions in cyberspace be meaningful ? ,[object Object],[object Object]
It’s been happening for years ,[object Object]
Places of ritual ,[object Object],[object Object],[object Object],[object Object]
Places of collaboration ,[object Object]
Places of friendship
So how does it happen ? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object]
Social Learning Theory ,[object Object],[object Object],[object Object],[object Object]
Social Capital ,[object Object],[object Object]
Building reputations ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
How the heck do you measure this? Social Network Analysis … studies social relationships as a series of interconnected webs. … focuses on inter-relationships rather than individuals’ attributes
SNA offers… ,[object Object],[object Object],[object Object]
SNA and friendship ,[object Object],[object Object],[object Object],[object Object]
Asking personal questions ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
N=675
[object Object],[object Object]
The micro-network: influence ,[object Object],[object Object],[object Object],[object Object]
Results: Single explanatory variable (General Communication) ,[object Object],*N=538; **N=539; σ 2 e : variance accounted for between avatars; T p<0.000, df=2 0.408 (0.027) 0.408 (0.027) 0.531 (0.035) 0.543 (0.035) σ 2 e 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
Single explanatory variable: General Trust & SNC categories ,[object Object],[object Object],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
Spare a thought for ethics ,[object Object],[object Object],[object Object],[object Object]
In Sum ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object]

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Social Networks in Virtual Worlds

  • 1. Social Networks in virtual worlds Aleks Krotoski University of Surrey
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  • 8. Places of friendship
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  • 14. How the heck do you measure this? Social Network Analysis … studies social relationships as a series of interconnected webs. … focuses on inter-relationships rather than individuals’ attributes
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  • 18. N=675
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