An agent for deception detection in discussion based environments

Amos Azaria, Ariella Richardson, Sarit Kraus

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

11 Scopus citations

Abstract

Extensive use of computerized forums and chat-rooms provides a modern venue for deception. We propose introducing an agent to assist in detecting and incriminating a deceptive participant. We designed a game, where deception in a text based discussion environment occurs. In this game several participants attempt to collectively detect a deceptive member. We compose an automated agent which participates in this game as a regular player. The goal of the agent is to detect the deceptive participant and alert other members, without raising suspicion itself. We use machine learning on the data collected from human players to design this agent. Extensive evaluation of our agent shows that it succeeds in raising the players collective success rate in catching the deceptive player.

Original languageEnglish
Title of host publicationCSCW 2015 - Proceedings of the 2015 ACM International Conference on Computer-Supported Cooperative Work and Social Computing
Pages218-227
Number of pages10
ISBN (Electronic)9781450329224
DOIs
StatePublished - 28 Feb 2015
Externally publishedYes
Event18th ACM International Conference on Computer-Supported Cooperative Work and Social Computing, CSCW 2015 - BC, Canada
Duration: 14 Mar 201518 Mar 2015

Publication series

NameCSCW 2015 - Proceedings of the 2015 ACM International Conference on Computer-Supported Cooperative Work and Social Computing

Conference

Conference18th ACM International Conference on Computer-Supported Cooperative Work and Social Computing, CSCW 2015
Country/TerritoryCanada
CityBC
Period14/03/1518/03/15

Keywords

  • Deception Detection
  • Human Agent Interaction
  • Machine Learning
  • SuspicionEvasion

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