Understanding Negotiation: A Text-Mining and NLP Approach to Virtual Interactions in a Simulation Game

Abstract

Negotiation constitutes a fundamental skill that applies to several daily life contexts; however, providing a reliable assessment and definition of it is still an open challenge. The aim of this research is to present an in-depth analysis of the negotiations occurring in a role-play simulation between users and virtual agents using Natural Language Processing. Users were asked to interact with virtual characters in a serious game that helps practice negotiation skills and to complete a psychological test that assesses conflict management skills on five dimensions. The dialogues of 425 participants with virtual agents were recorded, and a dataset comprising 4250 sentences was built. An analysis of the personal pronouns, word context, sentence length and text similarity revealed an overall consistency between the negotiation profiles and the user verbal choices. Integrating and Compromising users displayed a greater tendency to involve the other party in the negotiation using relational pronouns; on the other hand, Dominating individuals tended to use mostly single person pronouns, while Obliging and Avoiding individuals were shown to generally use fewer pronouns. Users with high Integrating and Compromising scores adopted longer sentences and chose words aimed at increasing the other party’s involvement, while more self-concerned profiles showed the opposite pattern.