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 simpl...社会互动是社会性动物的标志性行为特征。揭示此类行为表现中的特征模式，是行为生物学与心理学领域的核心研究方向之一，因其有助于推动对社会互动的全面理解、分类、预测乃至自动化实现。本研究提出一种用于探究社会互动特征模式的全新方法，可覆盖社会互动中的序列性行为与同步性行为两类形式。本分析的核心思路是将社会互动转化为行为状态序列，并聚焦于个体所展现的行为状态变化，而非行为状态的持续时长。我们拓展了数据挖掘与生物信息学领域的相关技术，用于检测此类序列中的频繁模式，并评估这些模式在个体间的差异，或是随互动任务变化的情况。为阐释本方法并展示其应用潜力，我们将其应用于一组简化的新型实验数据（原文结尾截断为“a simpl...”）