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

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.