Geo-spatial Domain Expertise in Microblogs

  • Wen Li
  • Carsten Eickhoff
  • Arjen P. de Vries
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8416)


In this paper, we present a framework for describing a user’s geo-spatial domain expertise in microblog settings. We investigate a novel way of casting the expertise problem by using points of interest (POI) as a possible categorization of expertise. To this end, we study a large-scale sample of geo-tagged tweets and model users’ location tracks in order to gain insights into their daily activities and competencies. Based on a qualitative user study among active Twitter users, we present an initial exploration of domain expertise indicators on microblogging portals and design a classification scheme that is able to reliably identify domain experts.


Domain expertise Geo-tagging Twitter 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Balog, K., Azzopardi, L., De Rijke, M.: Formal models for expert finding in enterprise corpora. In: SIGIR 2006, pp. 43–50. ACM (2006)Google Scholar
  2. 2.
    Banerjee, S., Dholakia, R.: Mobile advertising: does location based advertising work? International Journal of Mobile Marketing (2008)Google Scholar
  3. 3.
    Bar-Haim, R., Dinur, E., Feldman, R., Fresko, M., Goldstein, G.: Identifying and following expert investors in stock microblogs. In: EMNLP 2011, pp. 1310–1319 (2011)Google Scholar
  4. 4.
    Bennett, P.N., Radlinski, F., White, R.W., Yilmaz, E.: Inferring and using location metadata to personalize web search. In: SIGIR 2011, pp. 135–144. ACM (2011)Google Scholar
  5. 5.
    Campbell, C.S., Maglio, P.P., Cozzi, A., Dom, B.: Expertise identification using email communications. In: CIKM 2003, pp. 528–531 (2003)Google Scholar
  6. 6.
    Cheng, Z., Caverlee, J., Lee, K.: You are where you tweet: a content-based approach to geo-locating twitter users. In: CIKM 2010, pp. 759–768. ACM (2010)Google Scholar
  7. 7.
    Li, W., Serdyukov, P., de Vries, A.P., Eickhoff, C., Larson, M.: The where in the tweet. In: CIKM 2011, pp. 2473–2476. ACM (2011)Google Scholar
  8. 8.
    Wagner, C., Liao, V., Pirolli, P., Nelson, L., Strohmaier, M.: It’s Not in Their Tweets: Modeling Topical Expertise of Twitter Users. In: 2012 International Conference on Privacy, Security, Risk and Trust and 2012 International Confernece on Social Computing, pp. 91–100 (2012)Google Scholar
  9. 9.
    Weng, J., Lim, E.-P., Jiang, J., He, Q.: TwitterRank: Finding Topic-sensitive Influential Twitterers. In: WSDM 20210, pp. 261–270 (2010)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Wen Li
    • 1
  • Carsten Eickhoff
    • 2
  • Arjen P. de Vries
    • 3
  1. 1.Delft University of TechnologyDelftThe Netherlands
  2. 2.ETH ZurichZurichSwitzerland
  3. 3.Centrum Wiskunde & InformaticaAmsterdamThe Netherlands

Personalised recommendations