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Social Networks in virtual worlds

Social Networks in virtual worlds. Aleks Krotoski University of Surrey. Overview. The Social Life of Virtual Worlds What does it mean to be “ close ”? Informal learning in virtual worlds Who teaches who what? Important Ethical Concerns In research and in general practice.

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Social Networks in virtual worlds

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  1. Social Networks in virtual worlds Aleks Krotoski University of Surrey

  2. Overview • The Social Life of Virtual Worlds • What does it mean to be “close”? • Informal learning in virtual worlds • Who teaches who what? • Important Ethical Concerns • In research and in general practice

  3. But before we get ahead of ourselves… • The differences between online and offline: • Anonymity • Physical appearance • Physical proximity • Greater transience (more weak ties) • Absence of social cues

  4. So 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. It’s been happening for years • These virtual worlds are the places which the online communities are tied to

  6. Places of ritual London Memorial in Second Life • Between 12-1pm on 7 July 2005, over 150 Second Life residents visited. It was open for 7 days and racked up thousands of visitors • Fewer than 10% claimed any British ties • Maker’s motivations were altruistic and purely community-driven

  7. Places of collaboration Neualtenburg: an experiment in collective democracy

  8. Places of friendship

  9. So how does it happen? • The same reasons offline community does: • Make friends, offer support, meet like-minded others • What we know about online relationships: • Proximity and frequency of contact • Similarity • Self-presentation • Reciprocity & self-disclosure • Consistency

  10. Virtual worlds are designed for sociability – people must rely upon one another to survive and advance • Anonymity becomes Pseudonymity • Whatever role trust plays in offline communities, it plays in online communities because these interactions are human-bound

  11. Social Learning Theory • We learn from those around us • We learn from similar others • We adapt these learnings for our own goals • Social norms dictate acceptability

  12. Social Capital • We learn from those we trust • We learn who to trust through reputation

  13. Building reputations • Trust is based upon… • past experience… • …which is either based upon functional goals or pre-existing social relationships… • …or some kind of disinterested third party (e.g., Craig’s List or MySpace) • You Must Comply: • A non-official policing force in a space where an official police is absent • The emphasis is on friendship and dedication to the group • Rejection is cruel

  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

  15. SNA offers… • A measure of the social context, as defined by the actors within that context, rather than the researcher • Identification of key people for use as independent variables in social influence assessment • A map of the direction information will spread, including rate and possible barriers

  16. SNA and friendship • Who’s connected with whom? • How closely? • How many people are they connected with? • Who else is connected to this many people?

  17. Asking personal questions • Surveys • Who do you know? • Who do you communicate with? • Who do you trust? • Define your relationship: • Who’s trustworthy? (Poortinga & Pidgeon, 2003; Cvetkovich (1999); Renn & Levine, 1991) • Who’s credible? (Renn & Levine, 1991) • Who do you compare yourself with? (Lennox & Wolfe, 1984) • Who’s the most prototypical?

  18. N=675

  19. This N=75 • But what does it mean if someone’s considered “close” or “distant”?

  20. The micro-network: influence • Density • Position • Role • Direction

  21. Results: Single explanatory variable (General Communication) • The greatest prediction comes from general trust followed by credibility, which is not surprising, as this is proposed in Sherif’s (1981) contact hypothesis.

  22. Single explanatory variable: General Trust & SNC categories • 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.

  23. Spare a thought for ethics • Be transparent • Give something back • Talk to anyone who asks • Follow ethics guidelines (AoIR, UNESCO and others)

  24. In Sum • Closeness has implications for social learning, even in the virtual environment • Virtual communities operate in very similar ways to other communities – both on and offline • They bring together distributed individuals based on common experience, motivations and reputation • This is particularly true for virtual world participants because of the explicit social design of the software • Trust varies according to communication medium • Trust is paramount • Don’t jeopardise that trust.

  25. Thank you! E: A.Krotoski@surrey.ac.uk W: http://www.toaskid.com SL: Social Simulation Research Lab, Hyperborea

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