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Toward an Automatic Classification of Negotiation Styles Using Natural Language Processing

  • Daniela PacellaEmail author
  • Elena Dell’Aquila
  • Davide Marocco
  • Steven Furnell
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10498)

Abstract

We present a natural language processing model that allows automatic classification and prediction of the user’s negotiation style during the interaction with virtual humans in a 3D game. We collected the sentences used in the interactions of the users with virtual artificial agents and their associated negotiation style as measured by ROCI-II test. We analyzed the documents containing the sentences for each style applying text mining techniques and found statistical differences among the styles in agreement with their theoretical definitions. Finally, we trained two machine learning classifiers on the two datasets using pre-trained Word2Vec embeddings.

Keywords

Natural language Classification Virtual artificial agents Negotiation 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Daniela Pacella
    • 1
    Email author
  • Elena Dell’Aquila
    • 1
  • Davide Marocco
    • 2
  • Steven Furnell
    • 1
  1. 1.Centre for Robotics and Neural SystemsPlymouth UniversityPlymouthUK
  2. 2.Natural and Artificial Cognition LaboratoryUniversity of Naples Federico IINaplesItaly

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