Searching for expertise in social networks: a simulation of potential strategies
GROUP '05: Proceedings of the 2005 international ACM SIGGROUP conference on Supporting group work, page 71--80. New York, NY, USA, ACM Press, (2005)DOI: http://doi.acm.org/10.1145/1099203.1099214
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.
Description
e.g. Mark S. Ackerman, EECS and School of Information University of Michigan Ann Arbor, MI, 48109
URL http://www-personal.si.umich.edu/~junzh/papers/fp50-zhang.pdf
