The recent polarization of opinions in society has triggered a lot of research into the mechanisms involved. Personalized recommender systems embedded into social networks and online media have been hypothesized to contribute to polarisation, through a mechanism known as algorithmic bias. In recent work 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 enhanced this model by adding the biased interaction with media, in an effort to understand whether this facilitates polarisation. Media interaction are modelled as external fields that affect the population of individuals. Furthermore, we will study whether moderate media can be effective in counteracting polarisation.