Recent findings showed that users on Facebook tend to select information= that adhere to their system of beliefs and to form polarized groups - i.e.= , echo chambers. Such a tendency dominates information cascades and might a= ffect public debates on social relevant issues. In this work we explore the= structural evolution of communities of interest by accounting for users em= otions and engagement. Focusing on the Facebook pages reporting on scientif= ic and conspiracy content, we characterize the evolution of the size of the= two communities by fitting daily resolution data with three growth models = - i.e. the Gompertz model, the Logistic model, and the Log-logistic model. = Although all the models appropriately describe the data structure, the Logi= stic one shows the best fit. Then, we explore the interplay between emotion= al state and engagement of users in the group dynamics. Our findings show t= hat communities' emotional behavior is affected by the users' involvement i= nside the echo chamber. Indeed, to an higher involvement corresponds a more= negative approach. Moreover, we observe that, on average, more active user= s show a faster shift towards the negativity than less active ones.

Echo Chambers: Emotional Contagion and Group Polarization on Facebook

Caldarelli G;
2016-01-01

Abstract

Recent findings showed that users on Facebook tend to select information= that adhere to their system of beliefs and to form polarized groups - i.e.= , echo chambers. Such a tendency dominates information cascades and might a= ffect public debates on social relevant issues. In this work we explore the= structural evolution of communities of interest by accounting for users em= otions and engagement. Focusing on the Facebook pages reporting on scientif= ic and conspiracy content, we characterize the evolution of the size of the= two communities by fitting daily resolution data with three growth models = - i.e. the Gompertz model, the Logistic model, and the Log-logistic model. = Although all the models appropriately describe the data structure, the Logi= stic one shows the best fit. Then, we explore the interplay between emotion= al state and engagement of users in the group dynamics. Our findings show t= hat communities' emotional behavior is affected by the users' involvement i= nside the echo chamber. Indeed, to an higher involvement corresponds a more= negative approach. Moreover, we observe that, on average, more active user= s show a faster shift towards the negativity than less active ones.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11771/3482
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