Keyword extraction for social snippets

Zhenhui Li, Ding Zhou, Yun Fang Juan, Jiawei Han

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Today, a huge amount of text is being generated for social purposes on social networking services on the Web. Unlike traditional documents, such text is usually extremely short and tends to be informal. Analysis of such text benefit many applications such as advertising, search, and content filtering. In this work, we study one traditional text mining task on such new form of text, that is extraction of meaningful keywords. We propose several intuitive yet useful features and experiment with various classification models. Evaluation is conducted on Facebook data. Performances of various features and models are reported and compared.

Original languageEnglish (US)
Title of host publicationProceedings of the 19th International Conference on World Wide Web, WWW '10
Number of pages2
StatePublished - Jul 20 2010
Event19th International World Wide Web Conference, WWW2010 - Raleigh, NC, United States
Duration: Apr 26 2010Apr 30 2010

Publication series

NameProceedings of the 19th International Conference on World Wide Web, WWW '10


Other19th International World Wide Web Conference, WWW2010
Country/TerritoryUnited States
CityRaleigh, NC


  • keyword extraction
  • online advertising
  • social snippets

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications


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