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Longitudinal Affective Computing

Virtual Agents That Respond to User Mood

  • Conference paper
Intelligent Virtual Agents (IVA 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7502))

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Abstract

We present two empirical studies which examine user mood in long-term interaction with virtual conversational agents. The first study finds evidence for mood as a longitudinal construct independent of momentary affect and demonstrates that mood can be reliably identified by human judges observing user-agent interactions. The second study demonstrates that mood is an important consideration for virtual agents designed to persuade users, by showing that favors are more persuasive than direct requests when users are in negative moods, while direct requests are more persuasive for users in positive moods.

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Ring, L., Bickmore, T., Schulman, D. (2012). Longitudinal Affective Computing. In: Nakano, Y., Neff, M., Paiva, A., Walker, M. (eds) Intelligent Virtual Agents. IVA 2012. Lecture Notes in Computer Science(), vol 7502. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33197-8_9

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  • DOI: https://doi.org/10.1007/978-3-642-33197-8_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33196-1

  • Online ISBN: 978-3-642-33197-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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