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Social Networks in virtual worlds

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The Social Life of Virtual Worlds. What does it mean to be 'close' ... or some kind of disinterested third party (e.g., Craig's List or MySpace) You Must Comply: ... – PowerPoint PPT presentation

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Title: Social Networks in virtual worlds


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,
    thered be no such thing in cyberspace
  • How can you develop meaningful relationships with
    people youve never met?

5
Its 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
  • Makers 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.,
    Craigs 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
  • Whos 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
  • Whos trustworthy? (Poortinga Pidgeon, 2003
    Cvetkovich (1999) Renn Levine, 1991)
  • Whos credible? (Renn Levine, 1991)
  • Who do you compare yourself with? (Lennox
    Wolfe, 1984)
  • Whos the most prototypical?

18
N675
19
  • This N75
  • But what does it mean if someones 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 Sherifs (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
  • Dont jeopardise that trust.

25
  • Thank you!
  • E A.Krotoski_at_surrey.ac.uk
  • W http//www.toaskid.com
  • SL Social Simulation Research Lab, Hyperborea
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