Helpful or hierarchical? Predicting the communicative strategies of chat participants, and their impact on success

Farzana Rashid, Tommaso Fornaciari, Dirk Hovy, Eduardo Blanco, Fernando Vega-Redondo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

When interacting with each other, we motivate, advise, inform, show love or power towards our peers. However, the way we interact may also hold some indication on how successful we are, as people often try to help each other to achieve their goals. We study the chat interactions of thousands of aspiring entrepreneurs who discuss and develop business models. We manually annotate a set of about 5,500 chat interactions with four dimensions of interaction styles (motivation, cooperation, equality and advice). We find that these styles can be reliably predicted, and that the communication styles can be used to predict a number of indices of business success. Our findings indicate that successful communicators are also successful in other domains.

Original languageEnglish (US)
Title of host publicationFindings of the Association for Computational Linguistics Findings of ACL
Subtitle of host publicationEMNLP 2020
PublisherAssociation for Computational Linguistics (ACL)
Pages2366-2371
Number of pages6
ISBN (Electronic)9781952148903
StatePublished - 2020
Externally publishedYes
EventFindings of the Association for Computational Linguistics, ACL 2020: EMNLP 2020 - Virtual, Online
Duration: Nov 16 2020Nov 20 2020

Publication series

NameFindings of the Association for Computational Linguistics Findings of ACL: EMNLP 2020

Conference

ConferenceFindings of the Association for Computational Linguistics, ACL 2020: EMNLP 2020
CityVirtual, Online
Period11/16/2011/20/20

ASJC Scopus subject areas

  • Information Systems
  • Computer Science Applications
  • Computational Theory and Mathematics

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