Social cue detection and analysis using transfer entropy

Haoyang Jiang, Elizabeth A. Croft, Michael G. Burke

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


Robots that work close to humans need to understand and use social cues to act in a socially acceptable manner. Social cues are a form of communication (i.e., information flow) between people. In this paper, a framework is introduced to detect and analyse a class of perceptible social cues that are nonverbal and episodic, and the related information transfer using an information-theoretic measure, namely, transfer entropy. We use a group-joining setting to demonstrate the practicality of transfer entropy for analysing communications between humans. Then we demonstrate the framework in two settings involving social interactions between humans: object-handover and person-following. Our results show that transfer entropy can identify information flows between agents and when and where they occur. Potential applications of the framework include information flow or social cue analysis for interactive robot design and socially-aware robot planning.

Original languageEnglish
Title of host publicationProceedings of the 2024 ACM/IEEE International Conference on Human-Robot Interaction
EditorsWendy Ju, Harold Soh, Tom Williams
Place of PublicationNew York NY USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages10
ISBN (Electronic)9798400703225
Publication statusPublished - 2024
EventAnnual ACM/IEEE International Conference on Human-Robot Interaction (HRI) 2024 - Boulder, United States of America
Duration: 11 Mar 202415 Mar 2024
Conference number: 19th (Proceedings) (Website)


ConferenceAnnual ACM/IEEE International Conference on Human-Robot Interaction (HRI) 2024
Abbreviated titleHRI 2024
Country/TerritoryUnited States of America
Internet address


  • Nonverbal communication
  • Social cues
  • Socially-aware robots
  • Transfer entropy

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