Skip to main navigation Skip to search Skip to main content

An adaptive network model for interpersonal emotion regulation in multimodal human-bot interaction

  • Edgar Eler
  • , Jan Treur*
  • , Sophie C.F. Hendrikse
  • , Tara Donker
  • , Sander L. Koole
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Abstract

This paper provides and analyses a model and simulated data about human-bot interaction to help guide designers in assessing to what extent mapping human-like mental processes and behaviors on their companion bots has valuable effects. The analysis results found here provide a promising perspective for interpersonal emotion regulation using such human-like bots. The bot's multimodal interactions helped to regulate the human’s emotions by effects of emerging synchrony during the interaction even under less favorable situations such as poor individual emotion regulation capabilities.
Original languageEnglish
Title of host publicationComputational collectiveintelligence
Subtitle of host publication16th international conference, ICCCI 2024, Leipzig, Germany, September 9–11, 2024, proceedings, part II
EditorsNgoc Thanh Nguyen, Bogdan Franczyk, André Ludwig, Manuel Núñez, Jan Treur, Gottfried Vossen, Adrianna Kozierkiewicz
PublisherSpringer Cham
Pages67-79
Volume2
ISBN (Electronic)9783031708190
ISBN (Print)9783031708183
DOIs
Publication statusPublished - 31 Aug 2024
Externally publishedYes

Publication series

NameLecture notes in computer science
PublisherSpringer Cham
Volume14811
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Keywords

  • Interpersonal Emotion Regulation
  • Multimodal Interaction
  • Adaptive Network Model
  • Human-Bot Interaction

Fingerprint

Dive into the research topics of 'An adaptive network model for interpersonal emotion regulation in multimodal human-bot interaction'. Together they form a unique fingerprint.

Cite this