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Updated: Jan 21, 2026

The HoneyComb Paradigm for Research on Collective Human Behavior
Published on: January 19, 2019
Transfer entropy for synchronized behavior estimation of interpersonal relationships in human communication:
Kenji Takamizawa1, Masahiro Kawasaki2
1Department of Intelligent Interaction Technology, Graduate School of Systems and Information Engineering, University of Tsukuba, 1-1-1, Tennodai, Tsukuba-shi, Ibaraki, 305-8573, Japan.
Abstract:
A person's behavioral rhythms are synchronized spontaneously and unconsciously with those of other people, which often have positive effects, such as facilitating cooperation on tasks and promoting empathy for others. Although synchronization is induced by mutual interaction, it is unclear whether both individuals have the same influence. Is there a division of roles, in which some people are leaders and some followers? To address this, we calculated the transfer entropy (TE) of behavioral rhythms in a two-person cooperative tapping task, which provides an estimate of the direction of information propagation between two systems. We used TE to identify the causal relationship between two people (leader and follower); that is, the significant differences in the TE from one partner to another and vice versa. In this study, if there was a high TE from one individual (e.g., participant A) to the other individual (e.g., participant B), we defined participant A as the leader group and B as the follower group. First, using computer simulations, the programs which tapping intervals were almost independent with or were almost same with those of the partner programs were identified as the leader or follower, respectively, thereby confirming our hypothesis. Second, based on the results of the human experiment, we identified the leader and follower in some groups. Interestingly, the leader group showed a high systemizing quotient, which is related to communication deficits in developmental disorders such as autism. The results are consistent with participants' subjective impressions of their partners. Our methods can be used to estimate the interpersonal division of roles in complex human communications.
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