Privacy-Preserving Community-Aware Trending Topic Detection in Online Social Media

  • Theodore GeorgiouEmail author
  • Amr El Abbadi
  • Xifeng Yan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10359)


Trending Topic Detection has been one of the most popular methods to summarize what happens in the real world through the analysis and summarization of social media content. However, as trending topic extraction algorithms become more sophisticated and report additional information like the characteristics of users that participate in a trend, significant and novel privacy issues arise. We introduce a statistical attack to infer sensitive attributes of Online Social Networks users that utilizes such reported community-aware trending topics. Additionally, we provide an algorithmic methodology that alters an existing community-aware trending topic algorithm so that it can preserve the privacy of the involved users while still reporting topics with a satisfactory level of utility.



This work is supported by NSF grant CNS 1649469.


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Copyright information

© IFIP International Federation for Information Processing 2017

Authors and Affiliations

  1. 1.Department of Computer ScienceUniversity of California, Santa BarbaraSanta BarbaraUSA

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