A Comparison of Generated Wikipedia Profiles Using Social Labeling and Automatic Keyword Extraction

Authors

  • Terrell Russell University of North Carolina at Chapel Hill
  • Bongwon Suh Palo Alto Research Center
  • Ed Chi Palo Alto Research Center

Keywords:

Wikis (wikipedia), Expertise and authority discovery, Community identification

Abstract

In many collaborative systems, researchers are interested in creating representative user profiles. In this paper, we are particularly interested in using social labeling and automatic keyword extraction techniques for generating user profiles. Social labeling is a process in which users manually tag other users with keywords. Automatic keyword extraction is a technique that selects the most salient words to represent a user’s contribution. We apply each of these two profile generation methods to highly active Wikipedia editors and their contributions, and compare the results. We found that profiles generated through social labeling matches the profiles generated via automatic keyword extraction, and vice versa. The results suggest that user profiles generated from one method can be used as a seed or bootstrapping proxy for the other method.

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Published

2010-05-16

How to Cite

Russell, T., Suh, B., & Chi, E. (2010). A Comparison of Generated Wikipedia Profiles Using Social Labeling and Automatic Keyword Extraction. Proceedings of the International AAAI Conference on Web and Social Media, 4(1), 319-322. Retrieved from https://ojs.aaai.org/index.php/ICWSM/article/view/14058