A method for detecting characteristic patterns in social interactions with an application to handover interactions

Nikolai Bode, Andrew Sutton, Lindsey Lacey, John Fennell, Ute Leonards

Research output: Contribution to journalArticle (Academic Journal)peer-review

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Social interactions are a defining behavioural trait of social animals. Discovering characteristic patterns in the display of such behaviour is one of the fundamental endeavours in behavioural biology and psychology, as this promises to facilitate the general understanding, classification, prediction and even automation of social interactions. We present a novel approach to study characteristic patterns, including both sequential and synchronous actions in social interactions. The key concept in our analysis is to represent social interactions as sequences of behavioural states and to focus on changes in behavioural states shown by individuals rather than on the duration for which they are displayed. We extend techniques from data mining and bioinformatics to detect frequent patterns in these sequences and to assess how these patterns vary across individuals or changes in interaction tasks. To illustrate our approach and to demonstrate its potential, we apply it to novel data on a simple physical interaction, where one person hands a cup to another person. Our findings advance the understanding of handover interactions, a benchmark scenario for social interactions. More generally, we suggest that our approach permits a general perspective for studying social interactions.
Original languageEnglish
Article number160694
Number of pages16
JournalRoyal Society Open Science
Early online date18 Jan 2017
Publication statusPublished - Jan 2017

Structured keywords

  • Visual Perception
  • Cognitive Science


  • Social interactions
  • Interaction patterns
  • Social behaviour
  • Research methods
  • Subsequence mining


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