Information provenance in social media

  • Authors:
  • Geoffrey Barbier;Huan Liu

  • Affiliations:
  • Arizona State University, Data Mining and Machine Learning Laboratory;Arizona State University, Data Mining and Machine Learning Laboratory

  • Venue:
  • SBP'11 Proceedings of the 4th international conference on Social computing, behavioral-cultural modeling and prediction
  • Year:
  • 2011

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Abstract

Information appearing in social media provides a challenge for determining the provenance of the information. However, the same characteristics that make the social media environment challenging provide unique and untapped opportunities for solving the information provenance problem for social media. Current approaches for tracking provenance information do not scale for social media and consequently there is a gap in provenance methodologies and technologies providing exciting research opportunities for computer scientists and sociologists. This paper introduces a theoretical approach aimed guiding future efforts to realize a provenance capability for social media that is not available today. The guiding vision is the use of social media information itself to realize a useful amount provenance data for information in social media.