SWIM: fostering social network based information search

  • Authors:
  • Jun Zhang;Marshall Van Alstyne

  • Affiliations:
  • University of Michigan, Ann Arbor, MI;University of Michigan, Ann Arbor, MI

  • Venue:
  • CHI '04 Extended Abstracts on Human Factors in Computing Systems
  • Year:
  • 2004

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Abstract

Compare to searching online information directly, asking friends or finding referral to a human expert is preferred in many information-gathering tasks. It's easier to judge the quality of the information from a personal referral as well as to obtain information that is not publicly published [1]. Instant Messaging (IM) has potentials to effectively support such social network based information seeking [3], which are not fully explored other than providing better communications. For instance, a user usually does not know what his friends' friends know. If none of his friends in his IM buddy list knows the sought information, he either gives up this search method or needs intensive personal helps from a friend who transfers questions and answers in between.Previous studies indicated that it is feasible to add social network search functionalities to IM systems. Watts et al. [2] found that social networks have the surprising property of being searchable. Systems such as ReferralWeb [1], show that it is possible to mine people's social relationships and information identities from electronic resources and use them for referral or matchmaker purposes. Based on these ideas, we designed and implemented the Small World Instant Messenger (SWIM).