Investigating the effect of selective exposure, audience fragmentation, and echo-chambers on polarization in dynamic media ecosystems

Abstract

Abstract The degree of polarization in many societies has become a pressing concern in media studies. Typically, it is argued that the internet and social media have created more media producers than ever before, allowing individual, biased media consumers to expose themselves only to what already confirms their beliefs, leading to polarized echo-chambers that further deepen polarization. This work introduces extensions to the recent Cognitive Cascades model of Rabb et al. to study this dynamic, allowing for simulation of information spread between media and networks of variably biased citizens. Our results partially confirm the above polarization logic, but also reveal several important enabling conditions for polarization to occur: (1) the distribution of media belief must be more polarized than the population; (2) the population must be at least somewhat persuadable to changing their belief according to new messages they hear; and finally, (3) the media must statically continue to broadcast more polarized messages rather than, say, adjust to appeal more to the beliefs of their current subscribers. Moreover, and somewhat counter-intuitively, under these conditions we find that polarization is more likely to occur when media consumers are exposed to more diverse messages, and that polarization occurred most often when there were low levels of echo-chambers and fragmentation. These results suggest that polarization is not simply due to biased individuals responding to an influx of media sources in the digital age, but also a consequence of polarized media conditions within an information ecosystem that supports more diverse exposure than is typically thought.

Keywords

• Computational social science
• Polarization
• Media ecosystem
• Network science