Finding high-quality content in social media

Eugene Agichtein, Carlos Castillo, Debora Donato, Aristides Gionis, Gilad Mishne

Research output: Contribution to conferencePaper

743 Citations (Scopus)


The quality of user-generated content varies drastically from excellent to abuse and spam. As the availability of such content increases, the task of identifying high-quality content sites based on user contributions - social media sites - becomes increasingly important. Social media in general exhibit a rich variety of information sources: in addition to the content itself, there is a wide array of non-content information available, such as links between items and explicit quality ratings from members of the community. In this paper we investigate methods for exploiting such community feedback to automatically identify high quality content. As a test case, we focus on Yahoo! Answers, a large community question/answering portal that is particularly rich in the amount and types of content and social interactions available in it. We introduce a general classification framework for combining the evidence from different sources of information, that can be tuned automatically for a given social media type and quality definition. In particular, for the community question/answering domain, we show that our system is able to separate high-quality items from the rest with an accuracy close to that of humans.

Original languageEnglish
Number of pages11
Publication statusPublished - 6 May 2008
Event2008 International Conference on Web Search and Data Mining, WSDM 2008 - Palo Alto, CA, United States
Duration: 11 Feb 200812 Feb 2008


Other2008 International Conference on Web Search and Data Mining, WSDM 2008
CountryUnited States
CityPalo Alto, CA



  • Community question answering
  • Media
  • User interactions

ASJC Scopus subject areas

  • Information Systems
  • Signal Processing
  • Software
  • Theoretical Computer Science

Cite this

Agichtein, E., Castillo, C., Donato, D., Gionis, A., & Mishne, G. (2008). Finding high-quality content in social media. 183-193. Paper presented at 2008 International Conference on Web Search and Data Mining, WSDM 2008, Palo Alto, CA, United States.