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Searching for Expertise in Social Networks: A Simulation of Potential Strategies

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2005

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Proceedings of the 2005 ACM International Conference on Supporting Group Work

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Association for Computing Machinery

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.

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Zhang, Jun; Ackerman, Mark S. (2005): Searching for Expertise in Social Networks: A Simulation of Potential Strategies. Proceedings of the 2005 ACM International Conference on Supporting Group Work. DOI: 10.1145/1099203.1099214. New York, NY, USA: Association for Computing Machinery. pp. 71–80. Sanibel Island, Florida, USA

Keywords

CSCW, social networks, organizational simulations, expertise sharing, computer-supported cooperative work, expertise finding, information seeking, expertise location, social computing

Citation

DOI

10.1145/1099203.1099214

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URI

https://dl.eusset.eu/handle/20.500.12015/4856

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GROUP 2005

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Number of citations to item: 43

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