Polarization And Social Media A Systematic Review And Research Agenda

Bonisiwe Shabane

-Dec 6, 2025, 9:05 PM

polarization and social media a systematic review and research agenda

Scientific Reports volume 15, Article number: 35816 (2025) Cite this article The abundance of information on social media has reshaped public discussions, shifting attention to the mechanisms that drive online discourse. This study analyzes large-scale Twitter (now X) data from three global debates—Climate Change, COVID-19, and the Russo-Ukrainian War—to investigate the structural dynamics of engagement. Our findings reveal that discussions are not primarily shaped by specific categories of actors, such as media or activists, but by shared ideological alignment. Users consistently form polarized communities, where their ideological stance in one debate predicts their positions in others. This polarization transcends individual topics, reflecting a broader pattern of ideological divides.

Furthermore, the influence of individual actors within these communities appears secondary to the reinforcing effects of selective exposure and shared narratives. Overall, our results underscore that ideological alignment, rather than actor prominence, plays a central role in structuring online discourse and shaping the spread of information in polarized environments. The rapid expansion of social media has fundamentally changed the way people communicate, share information, and consume content. These platforms are now central to society, serving as tools for dissemination, entertainment, and consumption of information1,2,3,4. However, their engagement-driven business models and the dynamics of online interactions have raised concerns about their broader social impacts5,6, including their role in deepening polarization7,8,9, propagating misinformation10,11,12, and amplifying hate speech13,14,15,16,17. Moreover, recent research has highlighted the central role that the structure of social networks has in disseminating information18.

Building on these concerns, today’s digital environment is characterized by an overabundance of information, offering users an unprecedented range of choices for media consumption19. This shift results from the proliferation of various sources of content, fueling intense competition for user attention20,21,22, amplified by the engagement-driven strategies of social media platforms. Consequently, the information ecosystem has undergone a significant transformation, leading to a fragmented audience willing to participate23,24 but dispersed across numerous platforms and personalized feeds25. Traditional media gatekeepers, once central to public discourse, no longer unilaterally set the agenda26, diverging from previously dominant patterns of centralized media consumption27,28,29,30. This radical transformation has led to a vast and unstructured flow of content31 that may induce information overload32. Users often feel overwhelmed by the sheer volume of content when seeking information33, complicating their ability to navigate this landscape.

In this information-saturated ecosystem, online users increasingly exhibit selective consumption behaviors, engaging primarily with content aligned with their existing beliefs12,34,35 while ignoring opposing viewpoints36,37. This behavior reinforces echo chambers and exacerbates polarization8,38,39, in an environment where the value of news content is no longer determined solely by its intrinsic quality40. News consumption has become a shared social experience, with individuals exchanging links and recommendations within their networks and treating news as a form of cultural currency41. As a result, traditional hierarchical models of media influence struggle to explain the dynamics of public discourse in this decentralized environment42,43,44, where narratives and participants compete for prominence. As the access to this document is restricted, you may want to All material on this site has been provided by the respective publishers and authors.

You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:tefoso:v:183:y:2022:i:c:s0040162522004632. See general information about how to correct material in RePEc. If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form . If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation. New research shows the impact that social media algorithms can have on partisan political feelings, using a new tool that hijacks the way platforms rank content. How much does someone’s social media algorithm really affect how they feel about a political party, whether it’s one they identify with or one they feel negatively about? Until now, the answer has escaped researchers because they’ve had to rely on the cooperation of social media platforms.

New, intercollegiate research published Nov. 27 in Science, co-led by Northeastern University researcher Chenyan Jia, sidesteps this issue by installing an extension on consenting participants’ browsers that automatically reranks the posts those users see, in real time and still... Jia and her team discovered that after one week, users’ feelings toward the opposing party shifted by about two points — an effect normally seen over three years — revealing algorithms’ strong influence on...

Polarization And Social Media A Systematic Review And Research Agenda

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