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Measuring Non-cooperation in Dialogue

Plüss, Brian and Piwek, Paul (2016). Measuring Non-cooperation in Dialogue. In: Proceedings of the 26th International Conference on Computational Linguistics (COLING 2016), 11-16 Dec 2016, Osaka, Japan.

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This paper introduces a novel method for measuring non-cooperation in dialogue. The key idea is that linguistic non-cooperation can be measured in terms of the extent to which dialogue participants deviate from conventions regarding the proper introduction and discharging of conversational obligations (e.g., the obligation to respond to a question). Previous work on non-cooperation has focused mainly on non-linguistic task-related non-cooperation or modelled non-cooperation in terms of special rules describing non-cooperative behaviours. In contrast, we start from rules for normal/correct dialogue behaviour – i.e., a dialogue game – which in principle can be derived from a corpus of cooperative dialogues, and provide a quantitative measure for the degree to which participants comply with these rules. We evaluated the model on a corpus of political interviews, with encouraging results. The model predicts accurately the degree of cooperation for one of the two dialogue game roles (interviewer) and also the relative cooperation for both roles (i.e., which interlocutor in the conversation was most cooperative). Being able to measure cooperation has applications in many areas from the analysis – manual, semi and fully automatic – of natural language interactions to human-like virtual personal assistants, tutoring agents, sophisticated dialogue systems, and role-playing virtual humans.

Item Type: Conference or Workshop Item
Keywords: dialogue; natural language processing; cooperation; political interviews
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Research Group: Centre for Research in Computing (CRC)
Health and Wellbeing PRA (Priority Research Area)
Item ID: 47720
Depositing User: Paul Piwek
Date Deposited: 09 Nov 2016 16:15
Last Modified: 04 Jul 2020 01:28
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