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Strategies and language trends in learning success and failure of negotiation

Author

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  • Marina Sokolova

    (Université de Montréal)

  • Stan Szpakowicz

    (University of Ottawa
    Polish Academy of Sciences)

Abstract

In negotiation by electronic means, language is an important deal-making tool which helps realize negotiation strategies. Negotiators may use language to request information, exchange offers, persuade, threaten, as well as reach a compromise or find prospective partners. All this is recorded in texts exchanged by negotiators. We explore the language signals of strategies—argumentation, persuasion, negation, proposition. Leech and Svartvik’s approach to language in communication gives our study the necessary systematic background. It combines pragmatics, the communicative grammar and the meaning of English verbs. Language signals become features in the task of classifying those texts. We employ Statistical Natural Language Processing and Machine Learning techniques to find general trends that negotiation texts exhibit. Our hypothesis is that language signals help predict negotiation outcomes. We run experiments on the Inspire data. The electronic negotiation support system Inspire was gathering data for several years. The data include text messages which negotiators may exchange while trading offers. We conduct a series of Machine Learning experiments to predict the negotiation outcome from the texts associated with first halves of negotiations. We compare the results with the classification of complete negotiations. We conclude the paper with an analysis of the results and a list of suggestions for future work.

Suggested Citation

  • Marina Sokolova & Stan Szpakowicz, 2007. "Strategies and language trends in learning success and failure of negotiation," Group Decision and Negotiation, Springer, vol. 16(5), pages 469-484, September.
    • Handle: RePEc:spr:grdene:v:16:y:2007:i:5:d:10.1007_s10726-007-9083-9
    DOI: 10.1007/s10726-007-9083-9
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    References listed on IDEAS

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    1. Katharina J. Srnka & Sabine t. Koeszegi, 2007. "From Words to Numbers: How to Transform Qualitative Data into Meaningful Quantitative Results," Schmalenbach Business Review (sbr), LMU Munich School of Management, vol. 59(1), pages 29-57, January.
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    Cited by:

    1. Rudolf Vetschera, 2016. "Concessions Dynamics in Electronic Negotiations: A Cross-Lagged Regression Analysis," Group Decision and Negotiation, Springer, vol. 25(2), pages 245-265, March.
    2. Douglas P. Twitchell & Matthew L. Jensen & Douglas C. Derrick & Judee K. Burgoon & Jay F. Nunamaker, 2013. "Negotiation Outcome Classification Using Language Features," Group Decision and Negotiation, Springer, vol. 22(1), pages 135-151, January.

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