Recent polarisation of opinions in society has triggered a lot of research into the mechanisms involved. Personalised recommender systems embedded into social networks and online media have been hypothesized to contribute to polarisation, through a mechanism known as algorithmic bias. In a recent work [1] we have introduced a model of opinion dynamics with algorithmic bias, where interaction is more frequent between similar individuals, simulating the online social network environment. In this project we plan to enhance this model by adding the biased interaction with media, in an effort to understand whether this facilitates polarisation. Media interaction will be modelled as external fields that affect the population of individuals. Furthermore, we will study whether moderate media can be effective in counteracting polarisation.
[1] Sîrbu, A., Pedreschi, D., Giannotti, F. and Kertész, J., 2019. Algorithmic bias amplifies opinion fragmentation and polarization: A bounded confidence model. PloS one, 14(3), p.e0213246.


A paper on opinion dynamics in a complex systems or interdisciplinary journal.

Project Partners:

  • Consiglio Nazionale delle Ricerche, Pisa, Italy, Giulio Rossetti
  • Consiglio Nazionale delle Ricerche, Giulio Rossetti
  • Central European University, Janos Kertesz
  • University of Pisa, Alina Sirbu

Primary Contact: Giulio Rossetti, Consiglio Nazionale delle Ricerche, Pisa, Italy