Selective message distribution with people-tagging in user-collaborative environments

  • Authors:
  • Qihua Wang;Hongxia Jin

  • Affiliations:
  • Purdue University, West Lafayette, IN, USA;IBM Almaden Research Center, San Jose, CA, USA

  • Venue:
  • CHI '09 Extended Abstracts on Human Factors in Computing Systems
  • Year:
  • 2009

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Abstract

Oftentimes, we would like to distribute call-for-participation messages by email to people who are potentially interested in the topics of the corresponding events. Meanwhile, people either broadcast such messages to everyone in their organizations or maintain a number of mailing lists for different topics. But both approaches have drawbacks. In this paper, we explore the idea of automatically selecting recipients for broadcasting messages on different topics using people-tagging. In a collaborative people-tagging system, users can tag each other with the terms they want, and tags from different users are combined and aggregated. Tags applied to a user usually describe the user's attributes, such as her affiliation, expertise, and the projects she has been involved in. We can thus effectively find interested recipients by matching the content of messages with people's tags. A prototype of our solution has been implemented for a real-world and large-scale people-tagging system in IBM.