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SUMMARY:Towards a novel multi-scale integration of social dynamics and met
 abolic issues through evolutionary game theory on multiplex networks - Ale
 ssandro Di Stefano\, Dipartimento di Ingegneria Elettrica\, Elettronica e 
 Informatica (DIEEI) University of Catania
DTSTART:20181213T170000Z
DTEND:20181213T180000Z
UID:TALK116227@talks.cam.ac.uk
CONTACT:Pietro Lio
DESCRIPTION:As natural systems continuously evolve and become more increas
 ingly connected\, the recent advances in network science and complex syste
 ms open the way for deeply analysing\, identifying and quantifying the und
 erlying factors able to drive these networks. Multi-layer and multiplex ne
 tworks represent a major advance in the description of real-world social n
 etworks\, and have allowed to shed light on diffusion phenomena and the pr
 opagation of behaviours. Human beings live and interact through social mul
 tiplex networks\, so that behaviours and decisions are the result of more 
 complex cognitive reasons and connectedness on different spaces. Human coo
 peration dilemma becomes an even more challenging question\, thus one of t
 he main targets of our interdisciplinary research activity has been focusi
 ng 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 crit
 ical mass in the emergent dynamics. In order to analyse the evolutionary d
 ynamics\, the mathematical framework of Evolutionary Game Theory has been 
 taken into account\, considering the most common social dilemmas. Furtherm
 ore\, we have adopted a bio-inspired approach\, considering human-related 
 factors\, such as homophily\, heterogeneity\, micro-affirmations and micro
 -inequities. \nGut microbiota and human relationships are strictly connect
 ed to each other. What we eat reflects our body-mind connection and synchr
 onizes 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 investig
 ate the evolutionary dynamics of their interplay on a social multiplex net
 work. To quantify the complex dynamics of this interplay between gut and h
 uman behaviours\, we have explored the “gut-human behaviour axis” and 
 its evolutionary dynamics in a real-world scenario represented by the soci
 al multiplex network. We have defined a dual type of similarity\, homophil
 y and gut similarity\, other than psychological and unconscious biases. Th
 en\, 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 w
 ith the quality and quantity of food intake. Considering a population of s
 hift workers\, we have explored the dynamic interplay between their eating
  behaviours and gut microbiota\, modeling the social dynamics of chrono-nu
 trition in a multiplex network. \nOverall\, multi-layered networks allow u
 s 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 knowled
 ge\, 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 ga
 me-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 diff
 usion phenomena and emergent behaviours.
LOCATION:Department of Computer Science and technology\, sw01 
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