Unpublished,

Approximating Social Networks from Public Mailing Lists

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(2003)

Abstract

Online social networking tools may facilitate knowledge exchange by allowing users to share information and develop relationships with others near them in their social network. However maintaining complete, up-to-date social network information is challenging, requiring users to provide continuous, explicit access to their personal relationship data. We explore the viability of using public mailing lists in a corporate environment to automatically approximate social relationships. We found that co- memberships in mailing lists provided a reasonably accurate indication of who works with whom. We then explored whether people would find such social networking information valuable in seeking out or providing information to others. We found that organizational distance, social status, and informal social connections had a meaningful impact on whom users would chose to meet for sharing knowledge.

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