Psycholinguistic Features for Deceptive Role Detection in Werewolf

23438

Authors

nan

Abstract

We tackle the problem of identifying decep- tive agents in highly-motivated high-conflict dialogues. We consider the case where we only have textual information. We show the usefulness of psycho-linguistic deception and persuasion features on a small dataset for the game of Werewolf. We analyse the role of syntax and we identify some characteristics of players in deceptive roles. 1

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nan

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Proceedings of NAACL-HLT 2016, pages 417–422, San Diego, California, June 12-17, 2016. c⃝2016 Association for Computational Linguistics Psycholinguistic Features for Deceptive Role Detection in Werewolf ∗ Codruta Girlea University of Illinois Urbana, IL 61801, USA girlea2@illinois.edu Roxana Girju University of Illinois Urbana, IL 61801, USA girju@illinois.edu Eyal Amir University of Illinois Urbana, IL 61801, USA eyal@illinois.edu Abstract We tackle the problem of identifying decep- tive agents in highly-motivated high-conflict dialogues. We consider the case where we only have textual information. We show the usefulness of psycho-linguistic deception and persuasion features on a small dataset for the game of Werewolf. We analyse the role of syntax and we identify some characteristics of players in deceptive roles. 1 Introduction Deception detection has gained some attention in the NLP community (Mihalcea and Strapparava, 2009; Ott et al., 2011; Jindal and Liu, 2008). The focus has mostly been on detecting insincere reviews or argu- ments. However, there has been little work (Hung and Chittaranjan, 2010) in detecting deception and manipulation in dialogues. When the agents involved in a dialogue have con- flicting goals, they are often motivated to use decep- tion and manipulation in order to reach those goals. Examples include trials and negotiations. The high motivation for using deception and the possiblity of tracking the effects on participants throughout the dialogue sets this problem apart from identifying de- ception in nonce text fragment where motivation is not immediately relevant. The Werewolf game is an instance of such a di- alogue where people are motivated to deceive and ∗This research was partially funded owing to a collabora- tion between Adobe Research and the University of Illinois. We thank Julia Hockenmaier, Dan Roth, Dafna Shahaf, Walter Chang, Trung Bui, and our reviewers for their helpful comments and feedback. manipulate in order to reach their goals. The setting is a village where at least one of the villagers is se- cretly a werewolf. Each night, a villager falls prey to the werewolves. Each day, the remaining villagers discuss to find the most likely werewolf to execute. Players are assigned roles that define their goals and available actions. For our purpose, all roles are collapsed together as either werewolf or non- werewolf. There are other important roles in Were- wolf, such as seer, vigilante, etc, the goals and avail- able actions of which are not the focus of this paper. (Barnwell, 2012) provides a broader description of the game and roles. Each player only knows her own role, as assigned by an impartial judge who overlooks the game. The players with a werewolf role learn each other’s roles in the first round of the game. Every round, they pick another non-werewolf player to be removed from the game. This happens during a night phase, and is hidden from the other players. The judge announces the identity and role of the removed player. All players are then allowed to remove one other player from the game before the next night phase. They discuss and vote during a day …

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Labeled Text

We tackle the problem of identifying deceptive agents in highly-motivated high-conflict dialogues. We consider the case where we only have textual information. We show the usefulness of psycho-linguistic deception and persuasion features on a small dataset for the game of Werewolf. We analyse the role of syntax and we identify some characteristics of players in deceptive roles. 1

Publication Details

Paper ID:
23438
Year:
2016
Publication:
TIPSTER
Publication Type:
conf
DOI:
nan