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What Computers Can Tell Us About Emotions – Classification of Affective Communication in Electronic Negotiations by Supervised Machine Learning

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Group Decision and Negotiation. Theory, Empirical Evidence, and Application (GDN 2016)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 274))

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Abstract

Affective communication and emotions are an important part of negotiations. Negotiation support and negotiation support systems, however, tend to neglect this aspect given extant measurement difficulties. This study explores the possibilities of state of the art supervised machine learning techniques to classify emotions expressed in negotiation communication during electronic negotiation experiments. The affective content of the exchanged messages was determined by human coders and classified according to the circumflex model of affect. The output of this laborious activity, that can only be accomplished after a negotiation, which makes it irrelevant for negotiation support, was input to this study. Promising performance of some preprocessing and machine learning techniques was achieved. Especially the category of activating negative emotions, which is highly important in negotiations as it might reduce the prospects of reaching an agreement, was correctly classified quite often.

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Authors and Affiliations

  1. TU Wien, Institute of Management Science, Theresianumgasse 27, 1040, Vienna, Austria

    Michael Filzmoser, Sabine T. Koeszegi & Guenther Pfeffer

Authors
  1. Michael Filzmoser
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  2. Sabine T. Koeszegi
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  3. Guenther Pfeffer
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Corresponding author

Correspondence to Michael Filzmoser .

Editor information

Editors and Affiliations

  1. Western Washington University, Bellingham, Washington, USA

    Deepinder Bajwa

  2. TU Wien, Vienna, Austria

    Sabine T. Koeszegi

  3. University of Vienna, Vienna, Austria

    Rudolf Vetschera

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Filzmoser, M., Koeszegi, S.T., Pfeffer, G. (2017). What Computers Can Tell Us About Emotions – Classification of Affective Communication in Electronic Negotiations by Supervised Machine Learning. In: Bajwa, D., Koeszegi, S., Vetschera, R. (eds) Group Decision and Negotiation. Theory, Empirical Evidence, and Application. GDN 2016. Lecture Notes in Business Information Processing, vol 274. Springer, Cham. https://doi.org/10.1007/978-3-319-52624-9_9

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