The effects of online social media on critical issues, such as polarization and misinformation, are under scrutiny due to the disruptive consequences that these phenomena can have on our societies. Among the algorithms routinely used by social media platforms, people-recommender systems are of special interest, as they directly contribute to the evolution of the social network structure, affecting the information and the opinions users are exposed to. In this paper, we propose a novel framework to assess the effect of people recommenders on the evolution of opinions. Our proposal is based on Monte Carlo simulations combining link recommendation and opinion-dynamics models. In order to control initial conditions, we define a random network model to generate graphs with opinions, with tunable amounts of modularity and homophily. Finally, we join these elements into a methodology able to study the causal relationship between the recommender system and the echo chamber effect. Our method can also assess if such relationships are statistically significant. We also show how such a framework can be used to measure, by means of simulations, the impact of different intervention strategies. Our thorough experimentation shows that people recommenders can in fact lead to a significant increase in echo chambers. However, this happens only if there is considerable initial homophily in the network. Also, we find that if the network already contains echo chambers, the effect of the recommendation algorithm is negligible. Such findings are robust to two very different opinion dynamics models, a bounded confidence model and an epistemological model.

The effect of people recommenders on echo chambers and polarization / Cinus, Federico; Minici, Marco; Monti, Corrado; Bonchi, Francesco. - (2022), pp. 90-101. (Intervento presentato al convegno Proceedings of the Sixteenth International AAAI Conference on Web and Social Media ia (ICWSM2022) tenutosi a Atlanta, Georgia, USA) [10.1609/icwsm.v16i1.19275].

The effect of people recommenders on echo chambers and polarization

Federico Cinus
;
Francesco Bonchi
2022

Abstract

The effects of online social media on critical issues, such as polarization and misinformation, are under scrutiny due to the disruptive consequences that these phenomena can have on our societies. Among the algorithms routinely used by social media platforms, people-recommender systems are of special interest, as they directly contribute to the evolution of the social network structure, affecting the information and the opinions users are exposed to. In this paper, we propose a novel framework to assess the effect of people recommenders on the evolution of opinions. Our proposal is based on Monte Carlo simulations combining link recommendation and opinion-dynamics models. In order to control initial conditions, we define a random network model to generate graphs with opinions, with tunable amounts of modularity and homophily. Finally, we join these elements into a methodology able to study the causal relationship between the recommender system and the echo chamber effect. Our method can also assess if such relationships are statistically significant. We also show how such a framework can be used to measure, by means of simulations, the impact of different intervention strategies. Our thorough experimentation shows that people recommenders can in fact lead to a significant increase in echo chambers. However, this happens only if there is considerable initial homophily in the network. Also, we find that if the network already contains echo chambers, the effect of the recommendation algorithm is negligible. Such findings are robust to two very different opinion dynamics models, a bounded confidence model and an epistemological model.
2022
Proceedings of the Sixteenth International AAAI Conference on Web and Social Media ia (ICWSM2022)
organizational and group behavior mediated by social media; interpersonal communication mediated by social media; qualitative and quantitative studies of social media; human computer interaction; social media tools; navigation and visualization; social innovation and effecting change through social media
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
The effect of people recommenders on echo chambers and polarization / Cinus, Federico; Minici, Marco; Monti, Corrado; Bonchi, Francesco. - (2022), pp. 90-101. (Intervento presentato al convegno Proceedings of the Sixteenth International AAAI Conference on Web and Social Media ia (ICWSM2022) tenutosi a Atlanta, Georgia, USA) [10.1609/icwsm.v16i1.19275].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1671316
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