skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


  • NSF Public Access
  • Search Results
  • Investigating the effect of selective exposure, audience fragmentation, and echo-chambers on polarization in dynamic media ecosystems
Title: Investigating the effect of selective exposure, audience fragmentation, and echo-chambers on polarization in dynamic media ecosystems
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.  more » « less
Award ID(s):
1934553
PAR ID:
10473454
Author(s) / Creator(s):
; ;
Publisher / Repository:
Springer Science + Business Media
Date Published:
Journal Name:
Applied Network Science
Volume:
8
Issue:
1
ISSN:
2364-8228
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; (, Health Security)
    null (Ed.)
    The coronavirus disease 2019 (COVID-19) pandemic has created substantial challenges for public health officials who must communicate pandemic-related risks and recommendations to the public. Their efforts have been further hampered by the politicization of the pandemic, including media outlets that question the seriousness and necessity of protective actions. The availability of highly politicized news from online platforms has led to concerns about the notion of ‘‘echo chambers,’’ whereby users are exposed only to information that conforms to and reinforces their existing beliefs. Using a sample of 5,000 US residents, we explored their information-seeking tendencies, reliance on conservative and liberal online media, risk perceptions, and mitigation behaviors. The results of our study suggest that risk perceptions may vary across preferences for conservative or liberal bias; however, our results do not support differences in the mitigation behavior across patterns of media use. Further, our findings do not support the notion of echo chambers, but rather suggest that people with lower information-seeking behavior may be more strongly influenced by politicized COVID-19 news. Risk estimates converge at higher levels of information seeking, suggesting that high information seekers consume news from sources across the political spectrum. These results are discussed in terms of their theoretical implications for the study of online echo chambers and their practical implications for public health officials and emergency managers. 
    more » « less
  2. ; ; ; ; ; (, Proceedings of the International AAAI Conference on Web and Social Media)
    Previous research has documented the existence of both online echo chambers and hostile intergroup interactions. In this paper, we explore the relationship between these two phenomena by studying the activity of 5.97M Reddit users and 421M comments posted over 13 years. We examine whether users who are more engaged in echo chambers are more hostile when they comment on other communities. We then create a typology of relationships between political communities based on whether their users are toxic to each other, whether echo chamber-like engagement with these communities has a polarizing effect, and on the communities' political leanings. We observe both the echo chamber and hostile intergroup interaction phenomena, but neither holds universally across communities. Contrary to popular belief, we find that polarizing and toxic speech is more dominant between communities on the same, rather than opposing, sides of the political spectrum, especially on the left; however, this mostly points to the collective targeting of political outgroups. 
    more » « less
  3. ; ; (, Psychological Review)
    We present a theory of belief dynamics that explains the interplay between internal beliefs in people’s minds and beliefs of others in their external social environments. The networks of belief theory goes beyond existing theories of belief dynamics in three ways. First, it provides an explicit connection between belief networks in individual minds and belief dynamics on social networks. The connection, absent from most previous theories, is established through people’s social beliefs or perceived beliefs of others. Second, the theory recognizes that the correspondence between social beliefs and others’ actual beliefs can be imperfect, because social beliefs are affected by personal beliefs as well as by the actual beliefs of others. Past theories of belief dynamics on social networks do not distinguish between perceived and actual beliefs of others. Third, the theory explains diverse belief dynamics phenomena parsimoniously through the differences in attention and the resulting felt dissonances in personal, social, and external parts of belief networks. We implement our theoretical assumptions in a computational model within a statistical physics framework and derive model predictions. We find support for our theoretical assumptions and model predictions in two large survey studies (N1 = 973, N2 = 669). We then derive insights about diverse phenomena related to belief dynamics, including group consensus and polarization, group radicalization, minority influence, and different empirically observed belief distributions. We discuss how the theory goes beyond different existing models of belief dynamics and outline promising directions for future research. 
    more » « less
  4. ; ; ; (, Proceedings of the National Academy of Sciences)
    The abundance of media options is a central feature of today’s information environment. Many accounts, often based on analysis of desktop-only news use, suggest that this increased choice leads to audience fragmentation, ideological segregation, and echo chambers with no cross-cutting exposure. Contrary to many of those claims, this paper uses observational multiplatform data capturing both desktop and mobile use to demonstrate that coexposure to diverse news is on the rise, and that ideological self-selection does not explain most of that coexposure. We show that mainstream media outlets offer the common ground where ideologically diverse audiences converge online, though our analysis also reveals that more than half of the US online population consumes no online news, underlining the risk of increased information inequality driven by self-selection along lines of interest. For this study, we use an unprecedented combination of observed data from the United States comprising a 5-y time window and involving tens of thousands of panelists. Our dataset traces news consumption across different devices and unveils important differences in news diets when multiplatform or desktop-only access is used. We discuss the implications of our findings for how we think about the current communication environment, exposure to news, and ongoing attempts to limit the effects of misinformation. 
    more » « less
  5. ; ; ; (, PLOS ONE)
    Cremonini, Marco (Ed.)
    Understanding the spread of false or dangerous beliefs—often called misinformation or disinformation—through a population has never seemed so urgent. Network science researchers have often taken a page from epidemiologists, and modeled the spread of false beliefs as similar to how a disease spreads through a social network. However, absent from those disease-inspired models is an internal model of an individual’s set of current beliefs, where cognitive science has increasingly documented how the interaction between mental models and incoming messages seems to be crucially important for their adoption or rejection. Some computational social science modelers analyze agent-based models where individuals do have simulated cognition, but they often lack the strengths of network science, namely in empirically-driven network structures. We introduce a cognitive cascade model that combines a network science belief cascade approach with an internal cognitive model of the individual agents as in opinion diffusion models as a public opinion diffusion (POD) model, adding media institutions as agents which begin opinion cascades. We show that the model, even with a very simplistic belief function to capture cognitive effects cited in disinformation study (dissonance and exposure), adds expressive power over existing cascade models. We conduct an analysis of the cognitive cascade model with our simple cognitive function across various graph topologies and institutional messaging patterns. We argue from our results that population-level aggregate outcomes of the model qualitatively match what has been reported in COVID-related public opinion polls, and that the model dynamics lend insights as to how to address the spread of problematic beliefs. The overall model sets up a framework with which social science misinformation researchers and computational opinion diffusion modelers can join forces to understand, and hopefully learn how to best counter, the spread of disinformation and “alternative facts.” 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email