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Social networks and information sharing

Social networks and information sharing. Lada Adamic. Outline. Individual contributors: Is narrow focus of benefit? Should they draw on knowledge in other disciplines? What motivates individuals to volunteer information? How does money and competition affect that motivation? The network:

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Social networks and information sharing

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  1. Social networks and information sharing Lada Adamic

  2. Outline • Individual contributors: • Is narrow focus of benefit? • Should they draw on knowledge in other disciplines? • What motivates individuals to volunteer information? • How does money and competition affect that motivation? • The network: • What role do social networks play in information diffusion? • Are online networks truthful and representative of trust? • The information: • How does information change as it diffuses?

  3. Knows Knowledge iN Focus and quality in knowledge contribution • study 4 knowledge contribution contexts • scholarly publications (1900-2008) • patents (1976-2006) • Q&A forums (Yahoo! Answers, Baidu, Naver) • Wikipedia • main finding: • focus trumps quantity in explaining quality of contribution Adamic, Wei, Yang, Nam, Clarkson, First Monday, 2010

  4. Focus and knowledge contribution PATENTS PAPERS WIKIPEDIA CQA

  5. Impact of information diffusion across communities • study scholarly citation networks (JSTOR, patents) • does drawing from other areas (i.e. citing outside one’s field) translate to having higher impact? • social sciences and humanities: no • natural sciences and patents: yes Shi, Adamic, Tseng, PLoS One, 2009

  6. Knowledge iN Motivation and quality in information sharing • Analyze 2.6 million questions, 4.6 million answers + 26 interviews of top answerers • Users who contribute more often and less intermittently contribute higher quality information • Users prefer to answer unanswered questions and to correct incorrect answers • What motivates individuals to contribute in online Q&A forums? • altruism • learning • competition (point system) Nam, Ackerman, & Adamic, CHI’2009

  7. Monetary incentives and contribution • Crowdsourcing: 120 translation tasks • all pay auction mechanism: participants contribute solutions, only 1 is selected to receive payment • price treatment: high, low • shill treatment: enter in our own solution as a user with or without prior success • results • monetary incentives incentivize spam(85% are machine translations) • higher pay yields better contributions • shills discourage other quality contributions Liu, Yang, Adamic, Chen

  8. Social dynamics of information in virtual spaces (e.g. Second Life) • Items diffusing through social network spread more rapidly but have limited range • Early adopters are distinct from connectors • Sellers who chat with customers enjoy more repeat business, but social interaction doesn’t scale Bakshy, Karrer Adamic EC’09, Bakshy,Simmons,Huffaker,Teng, Adamic, Best Paper @ ICWSM’10

  9. Can online social networks be used as a proxy of trust and reputation? • Goal: • Understand basis of trust and friendship • Understand causes of bias in online trust ratings • Data: • 600K CouchSurfing users, 3 million ratings • Amazon & Epinions ratings • Findings: • When ratings are public, and when there is potential for reciprocity, ratings are overlypositive Surfing a Web of Trust: Reputation and Reciprocity on CouchSurfing.com, SIN’09 I rate you. You rate me. Should we do so publicly? WOSN 2010

  10. Design choices ?

  11. Reciprocity in CouchSurfing • Public friendship ratings are more highly correlated (rho = 0.73) than private trust ratings (rho = 0.39)

  12. Can trust be equated with friendship? • Close friendship -> high trust • High trust -> variable friendship • Trust and friendship strengthen over time, but rate varies by individual

  13. Predicting trust (person to person “vouches”) • Trust is localized/contextual • Trust is not the same as friendship • Global metrics do not perform as well as local ones

  14. Even “truthful” ratings may be biased

  15. tracing information across the web How do memes change as they diffuse length sentiment content How does their diffusion/evolution depend on the underlying network structure? length of phrase duration in days Simple Polya’s urn model of copying ABCDEFGH CDEF BCDE DEF CDEF Simmons, Adar, Adamic

  16. For more information • http://netsi.org Networks research group at the School of Information, University of Michigan • ladamic@umich.edu • Students: • Xiaolin Shi (PhD 2009, now postdoc at Stanford) • Chun-Yuen Teng (current PhD student) • Matthew Simmons (current PhD student) • Xiao Wei (MSI 2010)

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