Despite living in a hyperconnected digital world, we are exposed to fewer diverse perspectives than ever before. Personalized social media feeds foster a sense of being informed, yet they fragment the information we receive, reinforcing existing viewpoints and narrowing our exposure.
“Specifically, the concern is that social media algorithms combine with tendencies to interact with like-minded others to create an environment that predominantly exposes users to congenial, opinion-reinforcing content to the exclusion of more diverse, opinion-challenging content” (Kitchens et al., 2020).
Building on these concerns, Adam Greenwood asked viewers to challenge themselves and imagine a world where everyone agreed about everything. He asked us to consider a scenario in which those who disagreed with us on politics, religion, and other matters could not be seen or heard. Greenwood noted, “With algorithms deciding who we see, meet and hear online, this is becoming a reality” (Greenwood, 2019). These concerns echo broader debates around echo chambers and filter bubbles, as explored by researchers such as Kitchens et al. (2020).
The Genesis of Echo Chambers and Filter Bubbles
Kitchens et al. (2020) approached the concepts of echo chambers and filter bubbles by examining their origins. These ideas originate from concerns over the role of technology and group dynamics in group polarization (Kitchens et al., 2020).
The authors highlight that former understandings of echo chambers and filter bubbles are reactionary and reductionist, “portray[ing] not the creation of an observable outcome, but rather the absence of an idealized one” (Kitchens et al., 2020).
Kitchens et al. (2020) also critique the binary assumption that individuals are either “in” or “out” of echo chambers and filter bubbles. A consideration of complex behaviors is critical to this conceptualization.
While Kitchens et al. (2020) do not provide single, concise definitions for echo chambers and filter bubbles, they identify two consistent features: a lack of information diversity and ideological segregation.
Defining Echo Chambers and Filter Bubbles
Haug et al. (2025) define echo chambers simply as spaces “where certain opinions are accepted, and others are discredited and silenced.”
…social media communities that focus on hot-button issues such as abortion, religion, race, politics, gender, taxation, gun safety, and other social issues are more likely to become echo chambers.
Haug et al., 2025
Filter bubbles occur when “algorithms inadvertently amplify ideological segregation by automatically recommending content an individual is likely to agree with” (Flaxman et al., 2016).
Unsplash, 2018
This leads to questions about how exposure diversity functions within our media landscape.
What is Exposure Diversity?
Moe et al. (2021) sought to empirically operationalize exposure diversity for the purposes of media policy regulation.
The researchers analyzed media repertoires, or “the entirety of media” an individual regularly uses, to “identify vulnerable groups that are currently in danger of being excluded from news and current affairs,” and readiness for public connection (Moe et al., 2021, p. 162). This analysis determined availability and structural, positional, and individual factors that may influence media use and, thus, exposure to diverse information (Moe et al., 2021).
Moe et al. (2021) defined exposure diversity as “the degree of diversity of news and current affairs providers in the media repertoire of different groups of citizens” (Moe et al., 2021, p. 163).
Echo Chambers and Filter Bubbles Limit Exposure Diversity
Echo chambers and filter bubbles develop as social media intensifies our tendency to engage mainly with like-minded individuals. This restricts exposure to differing viewpoints, resulting in intellectual isolation and polarization, and ultimately undermining informed public discourse by distorting reality.
Exposure diversity describes the desired outcome of media engagement. If we are to consume, our resource base should expand outside our usual bubbles, making for informed opinions on current affairs.
Keywords: exposure diversity, echo chamber, filter bubbles, intellectual isolation, polarization, concept explication
References
Flaxman, S., Goel, S., Roa, J.M. (2016). Filter Bubbles, Echo Chambers, and Online News Consumption. Public Opinion Quarterly, 80(1), 298–320. https://doi.org/10.1093/poq/nfw006
Greenwood, A. (2019 January). Challenge The Echo Chamber [Video]. TEDxRoyalTunbridgeWells. https://www.ted.com/talks/adam_greenwood_challenge_the_echo_chamber_jan_2019?utm_campaign=tedspread&utm_medium=referral&utm_source=tedcomshare
Haug, M., Maier, C., Gewald, H., & Weitzel, T. (2025). Supporting opinions to fit in: a spiral of silence-theoretic explanation for establishing echo chambers and filter bubbles on social media. Internet Research, 35(7), 30–51. https://doi.org/10.1108/INTR-03-2024-0413
Kitchens, B., Johnson, S. L., & Gray, P. (2020). Understanding Echo Chambers and Filter Bubbles: The Impact of Social Media on Diversification and Partisan Shifts in News Consumption. MIS Quarterly, 44(4), 1619–1649. https://doi-org.ezproxy.lib.ou.edu/10.25300/MISQ/2020/16371
Moe, H., Hovden, J.F., & Karppinen, K. (2021). Operationalizing exposure diversity. European
Journal of Communication, 36(2), 148-167. https://doi.org/10.1177/0267323120966849
Lindsay Ashford 