Skip to main content

IBM Cambridge Research Center

  Technical Report: Recommending Topics for Self-Descriptions in Online User Profiles

Recommending Topics for Self-Descriptions in Online User Profiles

Technical Report #:08-16
Author(s): Werner Geyer, Casey Dugan, David R Millen, Michael Muller, Jill Freyne

Abstract

A Collaborative User Experience Technical Report: more about CUE...

Traditional social networking sites allow users to enter responses to a set of predefined fields when populating their personal profiles. In the system discussed in this work, freeform ‘About You’ entries allow users to craft their own questions / topics. We found that this kind of flexibility often leads to low content contributions and infrequent updates. The ‘About You’ recommender system described in this paper differs from many recommender systems in that it recommends content for users to
create, rather than consume. We present empirical data from an experiment with 2,000 users of a social networking site during a one month period. Our findings suggest that users who receive recommendations create more entries and update them more over time. Further, using articulated social network information for
recommendations performed better than content-based matching.


Full Report


For more information, or to order a Technical Report, contact us.