Polarized News Media and the Polarization of the Electorate

An increasing amount of empirical evidence suggests that in democracies that usually divide into two camps during a campaign season, the news media environment is fragmented and polarized. An emerging concern is whether the electorate in such divided societies would be pulled by polarized news media outlets and become polarized as well. This study, employing a series of agent-based simulations that takes into account polarized news media, communication networks, and individual differences all together, explores the effect of a polarized news environment on increases in extremist opinions and in the proportion of individuals with divided communication networks. It also identifies circumstances under which individuals perceive division within their communication networks. The findings suggest that the effect of a polarized news media environment on polarizing the electorate may be overestimated, while the homogenizing effect of communication networks may be underestimated.

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The competitions of time-varying and constant loadings in asset pricing models: empirical evidence and agent-based simulations

Journal of Economic Interaction and Coordination ◽

10.1007/s11403-021-00337-2 ◽

2021 ◽

Author(s):

Hung-Wen Lin ◽

Jing-Bo Huang ◽

Kun-Ben Lin ◽

Shu-Heng Chen

Keyword(s):

Asset Pricing ◽

Empirical Evidence ◽

Time Varying ◽

Pricing Models ◽

Agent Based ◽

Asset Pricing Models ◽

Agent Based Simulations

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Diffusion and persistence of false rumors in social media networks: implications of searchability on rumor self-correction on Twitter

Journal of Business Economics ◽

10.1007/s11573-020-01022-9 ◽

2021 ◽

Author(s):

Kathrin Eismann

Keyword(s):

Social Media ◽

Agent Based ◽

Social Media Networks ◽

Agent Based Simulations

AbstractSocial media networks (SMN) such as Facebook and Twitter are infamous for facilitating the spread of potentially false rumors. Although it has been argued that SMN enable their users to identify and challenge false rumors through collective efforts to make sense of unverified information—a process typically referred to as self-correction—evidence suggests that users frequently fail to distinguish among rumors before they have been resolved. How users evaluate the veracity of a rumor can depend on the appraisals of others who participate in a conversation. Affordances such as the searchability of SMN, which enables users to learn about a rumor through dedicated search and query features rather than relying on interactions with their relational connections, might therefore affect the veracity judgments at which they arrive. This paper uses agent-based simulations to illustrate that searchability can hinder actors seeking to evaluate the trustworthiness of a rumor’s source and hence impede self-correction. The findings indicate that exchanges between related users can increase the likelihood that trustworthy agents transmit rumor messages, which can promote the propagation of useful information and corrective posts.

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