Belief Polarization with Multiple Information Sources

In this paper, I analyze belief polarization in an environment with multiple information sources. The agents receive signals from two sources with different information qualities. The model allows for sharing this firsthand information among a network of friends, after which the agents update their beliefs. The analysis aims to unveil trends in the shift of beliefs on a particular topic and the specific conditions that define the direction of this shift. The main result: if the agents don't know the true information qualities of the sources, then under specific conditions, their beliefs will deviate from the true state of the world. Specifically, the model analyzes how optimistic and pessimistic approaches to assessing information quality lead to belief shifts in different directions, as well as the effect of the composition of the friends network. When clusters of people have different approaches to assessing the quality, under the specific conditions analyzed in this paper, their beliefs will deviate in opposite directions, leading to more polarization in society.