Quantifying long-range correlations and 1/f patterns in a minimal experiment of social interaction

Bedia, M. G., Aguilera, M., Gomez, T., Larrode, D. G., & Seron, F. (2014). Quantifying long-range correlations and 1/f patterns in a minimal experiment of social interaction. Frontiers in Psychology, 5, 1281. doi:10.3389/fpsyg.2014.01281

Together with Manuel Bedia, Tomás Gómez, David Larrode and Francisco Serón we just published a new paper presenting our results in applying 1/f and long-range correlation measures in social interaction dynamics. The paper is based on the Perceptual Crossing experiment, a minimal experimental setting reducing social interaction to one dimension. We find that human-human interaction presents a signature of long-range correlations not present when humans interact with artificial agents. This difference in signatures is not found between the individual behaviour of humans and artificial agents, suggesting that the qualitative difference of genuine social engagement lies in a shared space of interaction rather than in individual behaviour.


About maguilera0

Miguel Aguilera is a Postdoctoral Research Fellow at the IAS Research Center for Life, Mind and Society at the University of the Basque Country. He has been a visiting researcher at the Cognitive Science Program at Indiana University and the Ikegami Lab in the Department of General Systems Studies at the University of Tokyo, and a postdoctoral fellow at the University of the University of Zaragoza and the University of the Balearic Islands. His research focuses on autonomy in biological and social systems from an interdisciplinary perspective, integrating insights from cognitive science, theoretical neuroscience, computational modeling, adaptive behaviour, and complex systems. It combines nonlinear and dynamical models, evolutionary algorithms, and mathematical analysis from dynamical systems, network and information theory, to generate and understand situated and embodied models of agency in the realms of artificial life and evolutionary robotics, computational neuroscience, collective intelligence practices and socio-technical systems.
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