Social Media - Algorithmic Distortions and Polarization

Doomscrolling

Doomscrolling is the act of spending an excessive amount of time on digital content that elicit negative emotions. The concept was coined around 2018, and became more widespread in the context of the COVID-19 pandemic. The World Health Organization (WHO) observed that the pandemic was accompanied by widespread misleading information, conspiracy theories, and false reports, which it referred to as an "infodemic".

Infinite scrolling

Infinite scrolling, also known as endless scrolling, is an approach to web design where new material is continually dynamically added to the bottom of the page as the user scrolls downward, leading to the apparent ability to scroll forever. This is in contrast to pagination, where material is divided into discrete pages.

Taming the endless scroll? Short-form videos, digital routines and neurocognitive outcomes in youth

Short-form videos (SFVs) deliver digital content in a way that sets them apart from other media. Concerns have arisen that such user interfaces may diminish attention, memory and emotional wellbeing in young people, yet evidence has not previously been synthesised for this demographic and in isolation from other media types. To assess the association between exposure to SFV-interfaces and neurocognitive outcomes in individuals aged $$\varvec{\le 25}$$years, and to appraise the certainty of this evidence. Following PRISMA and Cochrane guidelines, four databases (PubMed, PsycINFO, WoS, Cochrane Reviews) were searched (2015–2025). Of 1,498 records, 42 studies (N = 46,912; mean age = 16.8) met the PICOS criteria. Most were cross-sectional (88%), with two longitudinal, one EEG, and one MRI study. Risk of bias and quality were evaluated using GRADE. Heavy, unstructured SFV use (typically $$\varvec{\ge 4}$$h/day) was consistently associated with: small-to-moderate increases in inattention ($$\varvec{\beta \approx 0.30}$$) and impulsivity ($$\varvec{\beta \approx 0.25}$$); moderate reductions in working-memory span ($$\varvec{\beta \approx -0.75}$$) and self-regulation ($$\varvec{\beta \approx -0.45}$$); moderate elevations in anxiety ($$\varvec{\beta \approx 0.35}$$), depression ($$\varvec{\beta \approx 0.48}$$) and stress ($$\varvec{\beta \approx 0.32}$$); and a moderate-to-large surge in addiction symptoms ($$\varvec{\beta \approx 0.60}$$). Two cross-sectional imaging studies also reported associations between heavier short-video use and neurobiological measures. These included grey-matter volume differences in the orbitofrontal cortex and cerebellum, altered resting-state signal synchrony, and reduced P300 amplitudes. Protective factors included supportive environments, digital routines, and digital literacy. Consistent, albeit preliminary, evidence links excessive SFV watching to cognitive and emotional challenges in youth. Longitudinal and experimental studies are urgently needed, alongside trials of modifiable levers to reduce addiction-like use and related harms.

Trolling democracy: anonymity doesn’t cause conflicts, bad site design does

‘Don’t feed the trolls’, people on social media are told. By forcing people to use their real names online, the managers of online forums hope to shame trolls into silence. But, J…

KFF Tracking Poll on Health Information and Trust: Use of Social Media and AI For Health Information and Advice | KFF

This poll finds that about 3 in 10 adults turn to social media for health information and advice at least monthly. Community connection and the need for immediate answers are the top reasons why people are turning to these tools. Slim majorities of those who use social media for health are confident they can tell what is true, and relatively few take steps to check the information they receive.

The "Majority Illusion" in Social Networks

Individual’s decisions, from what product to buy to whether to engage in risky behavior, often depend on the choices, behaviors, or states of other people. People, however, rarely have global knowledge of the states of others, but must estimate them from the local observations of their social contacts. Network structure can significantly distort individual’s local observations. Under some conditions, a state that is globally rare in a network may be dramatically over-represented in the local neighborhoods of many individuals. This effect, which we call the “majority illusion,” leads individuals to systematically overestimate the prevalence of that state, which may accelerate the spread of social contagions. We develop a statistical model that quantifies this effect and validate it with measurements in synthetic and real-world networks. We show that the illusion is exacerbated in networks with a heterogeneous degree distribution and disassortative structure.

Political divides cut through marriages and families in the run-up to the 2024 election

For many Americans, politics has become far more personal, and divisive, than it once was. Now, in the run-up to the November election, that’s creating some friction within families. Tonight, Judy Woodruff looks at the impact of politics on marriages, dating and families as part of her ongoing series, America at a Crossroads.

The Birth of the Attention Economy

The rise of the cheap, daily newspaper in the 19th century remade how Americans engaged with the world.

The Noisy Room

Only 3% of social media users post toxic content — but Americans estimate 43%. An interactive essay.

The case against efficiency: friction in social media

Social media platforms frequently prioritize efficiency to maximize ad revenue and user engagement, often sacrificing deliberation, trust, and reflective, purposeful cognitive engagement in the process. This manuscript examines the potential of friction—design choices that intentionally slow user interactions—as an alternate approach. We present a case against efficiency as the dominant paradigm on social media and advocate for a complex systems approach to understanding and analyzing friction. Drawing from interdisciplinary literature, real-world examples, and industry experiments, we highlight the potential for friction to mitigate issues like polarization, disinformation, and toxic content without resorting to censorship. We propose a state space representation of friction to establish a multidimensional framework and language for analyzing the diverse forms and functions through which friction can be implemented. Additionally, we propose several experimental designs to examine the impact of friction on system dynamics, user behavior, and information ecosystems, each designed with complex systems solutions and perspectives in mind. Our case against efficiency underscores the critical role of friction in shaping digital spaces, challenging the relentless pursuit of efficiency and exploring the potential of thoughtful slowing.

The social media discourse of engaged partisans is toxic even when politics are irrelevant

Abstract Prevailing theories of partisan incivility on social media suggest that it derives from disagreement about political issues or from status competition between groups. This study—which analyzes the commenting behavior of Reddit users across diverse cultural contexts (subreddits)—tests the alternative hypothesis that such incivility derives in large part from a selection effect: Toxic people are especially likely to opt into discourse in partisan contexts. First, we examined commenting behavior across over 9,000 unique cultural contexts (subreddits) and confirmed that discourse is indeed more toxic in partisan (e.g. r/progressive, r/conservatives) than in nonpartisan contexts (e.g. r/movies, r/programming). Next, we analyzed hundreds of millions of comments from over 6.3 million users and found robust evidence that: (i) the discourse of people whose behavior is especially toxic in partisan contexts is also especially toxic in nonpartisan contexts (i.e. people are not politics-only toxicity specialists); and (ii) when considering only nonpartisan contexts, the discourse of people who also comment in partisan contexts is more toxic than the discourse of people who do not. These effects were not driven by socialization processes whereby people overgeneralized toxic behavioral norms they had learned in partisan contexts. In contrast to speculation about the need for partisans to engage beyond their echo chambers, toxicity in nonpartisan contexts was higher among people who also comment in both left-wing and right-wing contexts (bilaterally engaged users) than among people who also comment in only left-wing or right-wing contexts (unilaterally engaged users). The discussion considers implications for democratic functioning and theories of polarization.

‘Views’ are lies

You might think a “view” means you watched something. You’d be wrong.

Can We Fix Social Media? Testing Prosocial Interventions using Generative Social Simulation

Social media platforms have been widely linked to societal harms, including rising polarization and the erosion of constructive debate. Can these problems be mitigated through prosocial interventions? We address this question using a novel method - generative social simulation - that embeds Large Language Models within Agent-Based Models to create socially rich synthetic platforms. We create a minimal platform where agents can post, repost, and follow others. We find that the resulting following-networks reproduce three well-documented dysfunctions: (1) partisan echo chambers; (2) concentrated influence among a small elite; and (3) the amplification of polarized voices - creating a 'social media prism' that distorts political discourse. We test six proposed interventions, from chronological feeds to bridging algorithms, finding only modest improvements - and in some cases, worsened outcomes. These results suggest that core dysfunctions may be rooted in the feedback between reactive engagement and network growth, raising the possibility that meaningful reform will require rethinking the foundational dynamics of platform architecture.

Can We Fix Social Media? Testing Prosocial Interventions using Generative Social Simulation

Social media platforms have been widely linked to societal harms, including rising polarization and the erosion of constructive debate. Can these problems be mitigated through prosocial interventions? We address this question using a novel method - generative social simulation - that embeds Large Language Models within Agent-Based Models to create socially rich synthetic platforms. We create a minimal platform where agents can post, repost, and follow others. We find that the resulting following-networks reproduce three well-documented dysfunctions: (1) partisan echo chambers; (2) concentrated influence among a small elite; and (3) the amplification of polarized voices - creating a 'social media prism' that distorts political discourse. We test six proposed interventions, from chronological feeds to bridging algorithms, finding only modest improvements - and in some cases, worsened outcomes. These results suggest that core dysfunctions may be rooted in the feedback between reactive engagement and network growth, raising the possibility that meaningful reform will require rethinking the foundational dynamics of platform architecture.