Towards a novel multi-scale integration of social dynamics and metabolic issues through evolutionary game theory on multiplex networks

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• Alessandro Di Stefano, Dipartimento di Ingegneria Elettrica, Elettronica e Informatica (DIEEI) University of Catania
• Thursday 13 December 2018, 17:00-18:00
• Department of Computer Science and technology, sw01 .

If you have a question about this talk, please contact Pietro Lio.

As natural systems continuously evolve and become more increasingly connected, the recent advances in network science and complex systems open the way for deeply analysing, identifying and quantifying the underlying factors able to drive these networks. Multi-layer and multiplex networks represent a major advance in the description of real-world social networks, and have allowed to shed light on diffusion phenomena and the propagation of behaviours. Human beings live and interact through social multiplex networks, so that behaviours and decisions are the result of more complex cognitive reasons and connectedness on different spaces. Human cooperation dilemma becomes an even more challenging question, thus one of the main targets of our interdisciplinary research activity has been focusing on the evolutionary dynamics of human cooperation on multiplex networks, exploring how and why it happens, quantifying the impact of homophily among people and the selection of different spatial configurations of critical mass in the emergent dynamics. In order to analyse the evolutionary dynamics, the mathematical framework of Evolutionary Game Theory has been taken into account, considering the most common social dilemmas. Furthermore, we have adopted a bio-inspired approach, considering human-related factors, such as homophily, heterogeneity, micro-affirmations and micro-inequities. Gut microbiota and human relationships are strictly connected to each other. What we eat reflects our body-mind connection and synchronizes with people around us. However, how this impacts on gut microbiota and, conversely, how gut bacteria influence our dietary behaviours has not been explored yet. Recently, this has raised our interest to investigate the evolutionary dynamics of their interplay on a social multiplex network. To quantify the complex dynamics of this interplay between gut and human behaviours, we have explored the “gut-human behaviour axis” and its evolutionary dynamics in a real-world scenario represented by the social multiplex network. We have defined a dual type of similarity, homophily and gut similarity, other than psychological and unconscious biases. Then, we have analysed the dynamics of social and gut microbial communities, quantifying the impact of human behaviours on diets and gut microbiota and, backwards, through a control mechanism. Meal timing mechanisms and “chrono-nutrition” play a crucial role in feeding behaviours, along with the quality and quantity of food intake. Considering a population of shift workers, we have explored the dynamic interplay between their eating behaviours and gut microbiota, modeling the social dynamics of chrono-nutrition in a multiplex network. Overall, multi-layered networks allow us to deal with several aspects on various scales include both macroscopic and microscopic aspects in the investigation of the underlying mechanisms and the hidden dynamics of complex and collective phenomena. The proposed models based on social multiplexity are able to integrate data and knowledge, reducing the inherent complexity and, at the same time, allowing us to gain a better understanding of social phenomena, make predictions and design innovative strategies for ICT and society. Our goal is to propose a thought-provoking and novel methodological approach, that exploits a game-theoretical approach to get multi-scale integration of different macro-scale and micro-scale aspects, ranging from complex networks to metabolic issues, other than including psychological and cognitive biases, in the investigation and modeling of the social dynamics and propagation of diffusion phenomena and emergent behaviours.

This talk is part of the CL-CompBio series.

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