Making E Friends And Influencing People In Second Life

Making e-friends and influencing people in

Second LifeAleks Krotoski

University of SurreySPERI

What I’ll talk about

• Interpersonal relationships in cyberspace

• How I measure relationships in Second Life

• How relationships are defined

Before I get ahead of myself

• The differences between online and offline:– Anonymity– Physical appearance– Physical proximity– Greater transience (more weak ties)– Absence of social cues

• So how can we expect community to grow?

Online community I

• In traditional definitions of “community”, there’d be no such thing in cyberspace– Tied to place – To misquote AOL ads, how can you fall for

someone you’ve never met?

• But we know that’s not true– Chatrooms, forums, MySpace, Craig’s List,

London Memorial

• These virtual worlds are the places which the online communities are tied to

Online Communities I (cont)

• Transient and formal communities– London Memorial in the virtual world 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

Online community II

• Form for the same reasons offline communities do:– Make friends, provide motivation, offer support, meet

like-minded others

• Whatever role trust plays in offline communities, it plays in online communities because these interactions are human-bound

• What we know about online relationships– Proximity and frequency of contact– Similarity– Self-presentation– Reciprocity & self-disclosure– Consistency

• Perpetuity: don’t mess with the orc if you’ve already PO’d the governor.

Trust in virtual communities I: we’re all in it together

• Returning to Anonymity– Perceived similarity (levelling the

playing field)– No social cues, so lots of

uncertainty– Expectations of openness and

honesty engenders a culture of mutual sharing

• Relevant Social Psychological dimension of trust– Similarity of goals and values– Expectations of future interaction

Trust in virtual worlds III: Rep (cont)

• 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)

• And speaking of social networking applications, the same principles work in-world too

• Finally, 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

How measure friendships? Social Network Analysis

…studies social relationships as a series of interconnected webs.…focuses on inter-relationships rather than individuals’ attributes

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?

ResultsN (respondents)

= 33N (total

network) = 650

Picking apart communication network closeness

• But what does it mean in Second Life if someone in this community is rated “close” or “distant”?

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)

*N=538; **N=539; σ2e: variance accounted for between avatars; Tp<0.000, df=2

• The greatest prediction comes from general trust followed by credibility, which is not surprising, as this is proposed in Sherif’s (1981) contact hypothesis.

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.

In Sum• Closeness has implications for influence and

persuasion, 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

Thank you!Aleks Krotoski (Mynci Gorky)

[email protected]