Jun Zhang
Mark S. Ackerman
ABSTRACT
People search for people with suitable expertise all of the time in their social networks - to answer questions or provide help. Recently, efforts have been made to augment this searching. However, relatively little is known about the social characteristics of various algorithms that might be useful. In this paper, we examine three families of searching strategies that we believe may be useful in expertise location. We do so through a simulation, based on the Enron email data set. (We would be unable to suitably experiment in a real organization, thus our need for a simulation.) Our emphasis is not on graph theoretical concerns, but on the social characteristics involved. The goal is to understand the tradeoffs involved in the design of social network based searching engines.
- Ackerman, M. S., Pipek, V., Wulf, V. Sharing Expertise: Beyond Knowledge Management, MIT Press, Cambridge MA, 2003. Google Scholar
- Ackerman, M.S., Boster, J., Lutters, W., McDonald, D. Who's there? The knowledge mapping approximation project, in Ackerman, M. S., Pipek, V., Wulf, V. Sharing Expertise: Beyond Knowledge Management, MIT Press, Cambridge MA, 2002. Google ScholarDigital Library
- Adamic, L.A., and Adar. E. How to search a social network. Social Networks, 27(3), 2005, 187--203.Google ScholarCross Ref
- Adamic, L.A., Lukose, R.M., Puniyani, A.R., and Huberman, B.A. Search in power-law networks. Physics Review E, 64(46135), 2001.Google Scholar
- Axelrod, R. Advancing the Art of Simulation in the Social Science, Simulating Social Phenomena, 1997. Google ScholarDigital Library
- Bernard, H. R., Killworth, P. D., McCarty, C. Index: An informant-defined experiment in social structure. Social Forces, 61 (1), 1982, 99--133.Google ScholarCross Ref
- Burt, R.S. The network structure of social capital. Research in Organizational Behavior. JAI Press, 2000, forthcoming.Google Scholar
- Cohen, W. Enron Email Dataset, http://www-2.cs.cmu.edu/~enron/Google Scholar
- Dodds, P. S., Muhamad, R., Watts, D. J. An Experimental Study of Search in Global Social Networks. Science, 301, 2003, 827--829.Google Scholar
- Nardi, BA., Whittaker, S., and Schwarz, H. It's not what you know, it's who you know: work in the information age. First Monday, 5, 2000.Google Scholar
- Foner, L. Yenta: A multi-agent, referral-based matchmaking system. In Proceedings of the 1st International Conference on Autonomous Agents, 1997, 301--307. Google ScholarDigital Library
- Granovetter, S. The strength of weak ties. American Journal of Sociology, 78, 1973, 1360--80.Google ScholarCross Ref
- Hamming, R.W. Error-detecting and error-correcting codes, Bell System Technical Journal, 29(2), 1950, 147--160.Google ScholarCross Ref
- Hutchins, E. Cognition in the Wild, MIT Press, 1995.Google Scholar
- Kautz, H., Selman, B., and Shah, M. The hidden Web. AI Magazine, 18(2), 1997, 27--36.Google Scholar
- Killworth, P., and Bernard, H. Reverse small world experiment. Social Networks, 1, 1978, 159--192.Google ScholarCross Ref
- Kleinberg, J. Navigation in a small world. Nature, 406, 2000, 845.Google ScholarCross Ref
- McDonald, D. W. and Ackerman, M.S. Expertise Recommender: A Flexible Recommendation Architecture. Proceedings of the ACM Conference on Computer-Supported Cooperative Work (CSCW '00), 2000, 231--240. Google ScholarDigital Library
- Milgram, S. The small-world problem. Psychology Today, 1, 1967, 62--67.Google Scholar
- Newman, M.E.J. A measure of betweenness centrality based on random walks, Arxiv preprint cond-mat/0309045, 2003.Google Scholar
- Russell, S., and Norvig, P. Artificial Intelligence: A Modern Approach. Prentice-Hall, 1995. Google ScholarDigital Library
- Whittaker, S., Jones, Q., Terveen, L, Contact Management: Identifying Contacts to Support Long-Term Communication. Proceedings of the ACM Conference on Computer Supported Cooperative Work., 2002, 216--225. Google ScholarDigital Library
- Streeter, L.A. and Lochbaum, K.E., Who Knows: A System Based on Automatic Representation of Semantic Structure. RIAO, 1988, 380--388.Google Scholar
- Travers, J., Milgram, S., 1969. An experimental study of the small world problem. Sociometry, 32, 425--443.Google Scholar
- Wasserman, S., Faust, K., Iacobucci, D, and Granovetter, M. Social Network Analysis: Methods and Applications, Cambridge University, 1994, 130--142.Google Scholar
- Watts, D. J., Dodds, P. S., Newman, M. E. J. Identity and search in social networks. Science, 296, 2002, 1302--1305.Google ScholarCross Ref
- Wegner, B., Erber, R., and Rayomond, P. Transactive Memory in Close Relationships, Journal of Personality and Social Psychology, 61 (6), 1991, 923--929.Google ScholarCross Ref
- Yang, S. B., and Garcia-Molina, H. Improving search in peer-to-peer networks. In Proceedings of 22nd International Conference on Distributed Computing Systems, 2002, 5--14. Google ScholarDigital Library
- Yates, R.A, Ribeiro, B. Modern Information Retrieval. ACM Press/Addison-Wesley, 1999. Google ScholarDigital Library
- Yu, B., and Singh, M.P. Searching Social Networks, Proceedings of Second International Joint Conference on Autonomous Agents and Multi-Agent Systems, 2003, 65--72. Google ScholarDigital Library
- Yu, B., Venkatraman, M., and Singh, M.P. An Adaptive Social Network for Information Access: Theoretical and Experimental Results, Journal of the Applied Artificial Intelligence, 17 (1), 2003, 21--38.Google ScholarCross Ref
Index Terms
- Searching for expertise in social networks: a simulation of potential strategies
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