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 language | English |
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Title of host publication | CSCW 2015 - Proceedings of the 2015 ACM International Conference on Computer-Supported Cooperative Work and Social Computing |
Publisher | Association for Computing Machinery, Inc |
Pages | 218-227 |
Number of pages | 10 |
ISBN (Electronic) | 9781450329224 |
DOIs | |
State | Published - 28 Feb 2015 |
Event | 18th ACM International Conference on Computer-Supported Cooperative Work and Social Computing, CSCW 2015 - BC, Canada Duration: 14 Mar 2015 → 18 Mar 2015 |
Publication series
Name | CSCW 2015 - Proceedings of the 2015 ACM International Conference on Computer-Supported Cooperative Work and Social Computing |
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Conference
Conference | 18th ACM International Conference on Computer-Supported Cooperative Work and Social Computing, CSCW 2015 |
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Country/Territory | Canada |
City | BC |
Period | 14/03/15 → 18/03/15 |
Bibliographical note
Publisher Copyright:© 2015 ACM.
Funding
ERC grant #267523, and ARO grants W911NF0910206 and W911NF1110344.
Funders | Funder number |
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Army Research Office | W911NF1110344, W911NF0910206 |
European Commission | 267523 |
Keywords
- Deception Detection
- Human Agent Interaction
- Machine Learning
- SuspicionEvasion