Finding local experts on twitter Conference Paper uri icon


  • © Copyright 2014 by the International World Wide Web Conferences Steering Committee. We address the problem of identifying local experts on Twitter. Specifically, we propose a local expertise framework that integrates both users' topical expertise and their local authority by leveraging over 15 million geo-tagged Twitter lists. We evaluate the proposed approach across 16 queries coupled with over 2,000 individual judgments from Amazon Mechanical Turk. Our initial experiments find significant improvement over a naive local expert finding approach, suggesting the promise of exploiting geo-tagged Twitter lists for local expert finding.

author list (cited authors)

  • Cheng, Z., Caverlee, J., Barthwal, H., & Bachani, V.

editor list (cited editors)

  • Chung, C., Broder, A. Z., Shim, K., & Suel, T.

publication date

  • January 1, 2014 11:11 AM