Community Formation as a Byproduct of a Recommendation System: A Simulation Model for Bubble Formation in Social Media

We investigate the problem of the formation of communities of users that selectively exchange messages among them in a simulated environment. This closed community can be seen as the prototype of the bubble effect, i.e., the isolation of individuals from other communities. We develop a computational...

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Autores principales:	Franco Bagnoli, Guido de Bonfioli Cavalcabo’, Banedetto Casu, Andrea Guazzini
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	community formation filter bubble echo chamber recommendation systems social media agent-based simulations Information technology T58.5-58.64
Acceso en línea:	https://doaj.org/article/bfe70b22c53f42598888cac9c676f4ba
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id	oai:doaj.org-article:bfe70b22c53f42598888cac9c676f4ba
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spelling	oai:doaj.org-article:bfe70b22c53f42598888cac9c676f4ba2021-11-25T17:40:05ZCommunity Formation as a Byproduct of a Recommendation System: A Simulation Model for Bubble Formation in Social Media10.3390/fi131102961999-5903https://doaj.org/article/bfe70b22c53f42598888cac9c676f4ba2021-11-01T00:00:00Zhttps://www.mdpi.com/1999-5903/13/11/296https://doaj.org/toc/1999-5903We investigate the problem of the formation of communities of users that selectively exchange messages among them in a simulated environment. This closed community can be seen as the prototype of the bubble effect, i.e., the isolation of individuals from other communities. We develop a computational model of a society, where each individual is represented as a simple neural network (a perceptron), under the influence of a recommendation system that honestly forward messages (posts) to other individuals that in the past appreciated previous messages from the sender, i.e., that showed a certain degree of affinity. This dynamical affinity database determines the interaction network. We start from a set of individuals with random preferences (factors), so that at the beginning, there is no community structure at all. We show that the simple effect of the recommendation system is not sufficient to induce the isolation of communities, even when the database of user–user affinity is based on a small sample of initial messages, subject to small-sampling fluctuations. On the contrary, when the simulated individuals evolve their internal factors accordingly with the received messages, communities can emerge. This emergence is stronger the slower the evolution of individuals, while immediate convergence favors to the breakdown of the system in smaller communities. In any case, the final communities are strongly dependent on the sequence of messages, since one can get different final communities starting from the same initial distribution of users’ factors, changing only the order of users emitting messages. In other words, the main outcome of our investigation is that the bubble formation depends on users’ evolution and is strongly dependent on early interactions.Franco BagnoliGuido de Bonfioli Cavalcabo’Banedetto CasuAndrea GuazziniMDPI AGarticlecommunity formationfilter bubbleecho chamberrecommendation systemssocial mediaagent-based simulationsInformation technologyT58.5-58.64ENFuture Internet, Vol 13, Iss 296, p 296 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	community formation filter bubble echo chamber recommendation systems social media agent-based simulations Information technology T58.5-58.64
spellingShingle	community formation filter bubble echo chamber recommendation systems social media agent-based simulations Information technology T58.5-58.64 Franco Bagnoli Guido de Bonfioli Cavalcabo’ Banedetto Casu Andrea Guazzini Community Formation as a Byproduct of a Recommendation System: A Simulation Model for Bubble Formation in Social Media
description	We investigate the problem of the formation of communities of users that selectively exchange messages among them in a simulated environment. This closed community can be seen as the prototype of the bubble effect, i.e., the isolation of individuals from other communities. We develop a computational model of a society, where each individual is represented as a simple neural network (a perceptron), under the influence of a recommendation system that honestly forward messages (posts) to other individuals that in the past appreciated previous messages from the sender, i.e., that showed a certain degree of affinity. This dynamical affinity database determines the interaction network. We start from a set of individuals with random preferences (factors), so that at the beginning, there is no community structure at all. We show that the simple effect of the recommendation system is not sufficient to induce the isolation of communities, even when the database of user–user affinity is based on a small sample of initial messages, subject to small-sampling fluctuations. On the contrary, when the simulated individuals evolve their internal factors accordingly with the received messages, communities can emerge. This emergence is stronger the slower the evolution of individuals, while immediate convergence favors to the breakdown of the system in smaller communities. In any case, the final communities are strongly dependent on the sequence of messages, since one can get different final communities starting from the same initial distribution of users’ factors, changing only the order of users emitting messages. In other words, the main outcome of our investigation is that the bubble formation depends on users’ evolution and is strongly dependent on early interactions.
format	article
author	Franco Bagnoli Guido de Bonfioli Cavalcabo’ Banedetto Casu Andrea Guazzini
author_facet	Franco Bagnoli Guido de Bonfioli Cavalcabo’ Banedetto Casu Andrea Guazzini
author_sort	Franco Bagnoli
title	Community Formation as a Byproduct of a Recommendation System: A Simulation Model for Bubble Formation in Social Media
title_short	Community Formation as a Byproduct of a Recommendation System: A Simulation Model for Bubble Formation in Social Media
title_full	Community Formation as a Byproduct of a Recommendation System: A Simulation Model for Bubble Formation in Social Media
title_fullStr	Community Formation as a Byproduct of a Recommendation System: A Simulation Model for Bubble Formation in Social Media
title_full_unstemmed	Community Formation as a Byproduct of a Recommendation System: A Simulation Model for Bubble Formation in Social Media
title_sort	community formation as a byproduct of a recommendation system: a simulation model for bubble formation in social media
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/bfe70b22c53f42598888cac9c676f4ba
work_keys_str_mv	AT francobagnoli communityformationasabyproductofarecommendationsystemasimulationmodelforbubbleformationinsocialmedia AT guidodebonfiolicavalcabo communityformationasabyproductofarecommendationsystemasimulationmodelforbubbleformationinsocialmedia AT banedettocasu communityformationasabyproductofarecommendationsystemasimulationmodelforbubbleformationinsocialmedia AT andreaguazzini communityformationasabyproductofarecommendationsystemasimulationmodelforbubbleformationinsocialmedia
_version_	1718412129349926912

Community Formation as a Byproduct of a Recommendation System: A Simulation Model for Bubble Formation in Social Media

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