Information Sharing in Social Media

Information Sharing in Social Media

Xiao Weiin collaboration with Lada Adamic & NETSI Group

School of information, University of Michigan

MURI 07MURI 07

Research Projects

MURI 07MURI 07

1. Incentivizing individuals to meet each other’s information needs:User Behavior Dynamics: A Sustainable Mechanism Works for Baidu Knows

2. Building reputation and trust through online and offline interactions: Reputation and Reciprocity on CouchSurfing.com

3. Who is likely to contribute more valuable information? Individual Focus and Knowledge Contribution

4. Should one build on “local” information & knowledge or draw on other communities?Information Diffusion in Citation Networks

Ingredients in facilitating information sharing and trust building

MURI 07, University of MichiganMURI 07 – 1. User Behavior Dynamics: A Sustainable Mechanism Works for Baidu Knows MURI 07 – 1. User Behavior Dynamics: A Sustainable Mechanism Works for Baidu Knows

Seeking and Offering Expertise across Categories: A Sustainable Mechanism Works for Baidu Knows, ICWSM 09, San Jose.

Baidu Knows: • Largest Chinese QA site• Virtual-point knowledge market• Built-in community tools

Motivations & Research Questions:

• First study on this successful QA site• How virtual points can help incentivize knowledge sharing• Users’ adaptive behavior patterns

Dataset: • Full history of Q&A during Dec, 2007~May, 2008• 9.3 million questions (5.2 million of them are solved)• 2.7 million users with 17.2 million answers


Major Findings:

Answerers are incentivized by points, thus expertise can be better allocated to more important questions

Users allocate points differently among questions:e.g., different categories

Askers adjust price from initial question, and they can slightly improve the ability of buying answers per point

In order to ask, users are driven to answer. Users who both ask and answer contribute most.


Conclusion:

A reinforcement cycle forms: people contribute more, are rewarded, gain more experience, improve their performance

MURI 07, University of MichiganMURI 07 – 2. Surfing a Web of Trust: Reputation and Reciprocity on CouchSurfing.comMURI 07 – 2. Surfing a Web of Trust: Reputation and Reciprocity on CouchSurfing.com

Surfing a Web of Trust: Reputation and Reciprocity on CouchSurfing.com, SIN 09, Vancouver

Previous works on group level: • Bialski & Batorski (2006) examined which factors contribute to higher trust between CouchSurfing friends.

• Molz (2007) examined the sociological meaning of reciprocity in the context of hospitality exchanges.

Research Questions:Trust:

oWho is doing the vouching?oWho is being vouched for?oCan we predict which connections are vouched?

Dataset:600,000+ users, 1.5 million+ friendship connections


Major findings:

A high number of vouches are between “CouchSurfing friends”.

Friendship degree:1= Haven’t met yet2= Acquaintance3= CouchSurfing friend4= Friend5= Good friend6= Close friend7= Best friend


Major findings:

Conclusion:Friendship degree information is beneficialGlobal measures may be useful in assigning overall reputation scores, but not for predicting if a specific person will vouch for another or notFurther work is needed to determine if vouches are given too freely

Results from logistic regression for each variable alone:Global measures are poor predictors of whether an edge is vouched

Variable Predictive accuracy:

Friendship degree 67.7%

Shared friend 55.8%

2-step vouch propagation 54.2%

PageRank 50.6%

MURI 07, University of MichiganMURI 07 – 3. Individual Focus and Knowledge ContributionMURI 07 – 3. Individual Focus and Knowledge Contribution

Individual focus and knowledge contribution, working paper

Previous works on group level: • J. Katz, D. Hicks, Scientometrics 40, 541 (1997)• B. Jones, S. Wuchty, B. Uzzi, Science 322, 1259 (2008). • S. Wuchty, B. Jones, B. Uzzi, Science 316, 1036 (2007).• R. Guimera, B. Uzzi, J. Spiro, L. Amaral, Science 308, 697 (2005). • I. Rafols, M. Meyer, Scientometrics (2008). • S. Page, The difference: How the power of diversity creates better groups, firms, schools, and societies (Princeton University Press, 2007).

Motivations & Research Questions:

• First study on individual level• To study whether an individual’s diversity is beneficial.


Goal: To measure the relationship between the narrowness of focus and the quality of contribution of individuals across a range of knowledge sharing systems.

Approach: •Focus (Stirling measure):

•Quality:oPatents and Research Articles: Normalized citation countoWikipedia: New word contributed that survive revisionsoQ&A forum participant: Win rate

Datasets:

• JSTOR: 2 million articles plus 6.6 million citations•Patents: 5.5 million patents filed between 1976~2006•Q&A forums: Crawled data from Yahoo! Answers, Baidu Knows, Naver KnowledgeIN •Wikipedia: Meta-history dump file of the English Wikipedia generated on Nov. 4th, 2006, parsed 7% pages


Major findings:

Conclusion: Across all systems we observe a small but significant positive correlation between focus and quality.

MURI 07, University of MichiganMURI 07 – 4. Information Diffusion in Citation NetworksMURI 07 – 4. Information Diffusion in Citation Networks

Information Diffusion in Citation Networks.

Previous works: • Visualization and quantification of the amount of information flow between different areas in science [Boyack, 2005], [Bollen, 2009]. • Features of information flows in citation networks [Borner, 2004], [Rosvall, 2007].

• Effects of collaborations across different universities, and team collaborations [Katz, 1997], [Wuchty, 2007].

Research Questions:

What happens once information has diffused across a community boundary?

Shi X, Adamic LA, Tseng BL, Clarkson GS, 2009 The Impact of Boundary Spanning Scholarly Publications and Patents. PLoS ONE 4(8): e6547. doi:10.1371/journal.pone.0006547


Goal: To study information diffusion within vs. across communities and its subsequent impact.

Approach: •Studying citation networks: the social ecology of knowledge – where information is shared and flows along co-authorship and citation ties.•Articles/patents -> nodes; citations -> directed edges, from cited to citing•Communities: JSTOR -> Journal discipline; Patents -> Categories•Community proximity:

Datasets:

IBM patent citation network and JSTOR citation network

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Major findings:

Patent Natural science

Social science

Arts & humanities

Overall correlation

0.062*** -0.027*** 0.033*** 0.044***

Correlation after removing0 impact

-0.047*** -0.072*** 0.040*** -0.011*

*** and * denote significance at < 0.001 and > 0.05 level respectively.

Correlations between impact and community proximityCorrelations between impact and community proximity

Conclusion: A publication’s citing across disciplines is tied to its subsequent impact. While risking not being cited at all, patents and publications in the natural sciences are more likely be higher impact when they cite across community boundariesThere is no such effect in the social sciences and humanities.

If we focus on patents and natural science publications that have had at least a given level of impact, we consistently observe that citing across community boundaries leads to slightly higher impact.

Thank you!

further information:http://www-personal.umich.edu/~ladamic

http://weixiao.us/projects.html

http://www-personal.umich.edu/~ladamic

http://weixiao.us/projects.html

Documents

Information Sharing in Social Media