Behavioral Detection of Spam URL Sharing: Posting Patterns Versus Click Patterns Conference Paper uri icon

abstract

  • © 2014 IEEE. Social media systems like Twitter and Facebook provide a global infrastructure for sharing information, and in one popular direction, of sharing web hyperlinks. Understanding the behavioral signals of both how URLs are inserted into these systems (via posting by users) and how URLs are received by social media users (via clicking) can provide new insights into social media search, recommendation, and user profiling, among many others. Such studies, however, have traditionally been difficult due to the proprietary (and sometimes private) nature of much URL-related data. Hence, in this paper, we begin a behavioral examination of URL sharing through two distinct perspectives: (i) the first is via a study of how these links are posted through publicly-accessible Twitter data; (ii) the second is via a study of how these links are received by measuring their click patterns through the publicly-accessible Bitly click API. We examine the differences between posting and click patterns in a sample application domain: the classification of spam URLs. We find that these behavioral signals - posting versus clicking - provide overlapping but fundamentally different perspectives on URLs, and that these perspectives can inform the design of future applications of spam link detection and link sharing.

altmetric score

  • 0.25

author list (cited authors)

  • Cao, C., & Caverlee, J.

citation count

  • 12

editor list (cited editors)

  • Wu, X., Ester, M., & Xu, G.

publication date

  • August 2014

publisher