Online abusive users analytics through visualization

Anna C. Squicciarini, Jules Dupont, Ruyan Chen

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

3 Scopus citations

Abstract

In this demo, we present Abuse User Analytics (AuA), an analytical framework aiming to provide key information about the behavior of online social network users. AuA efficiently processes data from users' discussions, and renders information about users' activities in a easy to-understand graphical fashion with the goal of identifying deviant or abusive activities. Using animated graphics, AuA visualizes users' degree of abusiveness, measured by several key metrics, over user selected time intervals. It is therefore possible to visualize how users' activities lead to complex interaction networks, and highlight the degenerative connections among users and within certain threads.

Original languageEnglish (US)
Title of host publicationWWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web
PublisherAssociation for Computing Machinery, Inc
Pages155-158
Number of pages4
ISBN (Electronic)9781450327459
DOIs
StatePublished - Apr 7 2014
Event23rd International Conference on World Wide Web, WWW 2014 - Seoul, Korea, Republic of
Duration: Apr 7 2014Apr 11 2014

Publication series

NameWWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web

Other

Other23rd International Conference on World Wide Web, WWW 2014
CountryKorea, Republic of
CitySeoul
Period4/7/144/11/14

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Software

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