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Psychology & interventionsSpread & networks Cognitive reflection correlates with behavior on TwitterHigh scorers on the Cognitive Reflection Test (CRT)—a measure of analytical thinking—are more discerning social media users: they follow fewer accounts, share news from more reliable sources, and engage more with substantive topics like politics. The study identifies "cognitive echo chambers" where low-CRT users preferentially follow… Mosleh et al. · Nature Communications · 2021

Psychology & interventionsSpread & networks News literacy, social media behaviors, and skepticism toward information on social mediaA national survey of 788 Americans examines how news literacy relates to what people see and share on social media, and whether it predicts skepticism toward information shared in these spaces. The key finding: people with higher news literacy see and post less political content on social media, but when they do engage, they're… Vraga & Tully · Information, Communication & Society · 2021

Fact-checking & verificationPlatforms, policy & society Types, Sources, and Claims of COVID-19 MisinformationSystematic analysis of 225 fact-checked COVID-19 misinformation pieces reveals that most false content reconfigures existing information (59%) rather than fabricating entirely new claims. Public authorities are cited in 39% of misinformation, yet top-down claims from politicians and celebrities account for only 20% of volume but drive… Brennen et al. · Reuters Institute for the Study of… · 2020

Spread & networksPlatforms, policy & society Assessing the risks of 'infodemics' in response to COVID-19 epidemicsAnalysis of 112+ million geolocated Twitter messages about COVID-19 (January–March 2020) across 64 languages and countries. Develops an infodemic risk index (IRI) measuring exposure to unreliable news; demonstrates that waves of unreliable information precede pandemic waves, providing early-warning signals for policy intervention. Gallotti et al. · Nature Human Behaviour · 2020

Spread & networksPlatforms, policy & society Exposure to untrustworthy websites in the 2016 US electionUsing combined survey and web-traffic data from the 2016 US presidential election, Guess et al. found that while 44.3% of Americans aged 18+ visited an untrustworthy website during the campaign, actual exposure was highly concentrated among Trump supporters (56.7% of Trump supporters vs. 27.7% of Clinton supporters). Facebook played a… Guess et al. · Nature Human Behaviour · 2020

Spread & networksPlatforms, policy & society A first look at COVID-19 information and misinformation sharing on TwitterEarly-pandemic analysis of 21 million COVID-19 tweets showing Twitter conversations predict case increases by 2–5 days; identifies five prevalent myths (origin, flu comparison, heat, home remedies, vaccine) accounting for ~0.6% of tweets; finds most shared URLs point to reputable sources (CDC, WHO) rather than misinformation sites,… Singh et al. · arXiv · 2020

Spread & networksPlatforms, policy & society The Hype MachineA book talk by MIT's Sinan Aral on "The Hype Machine," which explores how social media simultaneously disrupts elections, the economy, and public health while offering tremendous potential for good. The presentation synthesizes 20 years of research on social media diffusion, arguing that misinformation spreads faster than truth because… Aral · 2020

Spread & networksPlatforms, policy & society Mis- and Disinformation During Crisis EventsKate Starbird, associate professor at UW's HCDE and co-founder of the Center for an Informed Public, discusses how misinformation and disinformation spread during crisis events, with case studies from the COVID-19 pandemic and 2020 election. She distinguishes between harmful misinformation (false but well-intentioned), disinformation… Starbird · University of Washington · 2020

LLMs & generative AIDetection methods TextAttack: A Framework for Adversarial Attacks, Data Augmentation, and Adversarial Training in NLPIntroduces TextAttack, an open-source Python framework unifying 16 adversarial attacks from the literature into a modular architecture for testing and improving NLP model robustness. The framework decomposes attacks into four reusable components (goal function, constraints, transformation, search method), enables benchmarking attacks on… Morris et al. · arXiv · 2020

LLMs & generative AIDetection methods A Survey of the State of Explainable AI for Natural Language ProcessingRecent neural NLP models achieve strong performance but are often opaque. This survey systematically reviews explainable AI (XAI) research in NLP across 50 papers from major conferences (2013–2019), categorizing explanations by scope (local vs. global) and generation (self-explaining vs. post-hoc), detailing five major techniques… Danilevsky et al. · arXiv · 2020

LLMs & generative AIPlatforms, policy & society Language Models are Few-Shot LearnersThis landmark paper introduces GPT-3, a 175-billion-parameter autoregressive language model, and demonstrates that it achieves strong performance on diverse NLP tasks through in-context few-shot learning without any task-specific fine-tuning. The model exhibits remarkable scaling properties where larger models dramatically improve… Brown et al. · NeurIPS 2020 · 2020

Spread & networksPlatforms, policy & society The COVID-19 Social Media InfodemicComparative analysis of COVID-19 information diffusion across five social media platforms (Twitter, Instagram, YouTube, Reddit, Gab) using epidemic models. All platforms exhibit infodemic characteristics (basic reproduction number R₀ 1), with platform-dependent differences in how misinformation spreads relative to reliable information. Cinelli et al. · arXiv · 2020

Bots & coordinated campaignsDatasets & evaluation A Decade of Social Bot DetectionA comprehensive review of social bot detection research from 2010 to 2020, documenting the evolution from supervised individual-account detection to group-level approaches targeting coordinated inauthentic behavior. The paper traces the escalating "arms race" between bot developers and detection researchers, illustrates bots' documented… Cresci · Communications of the ACM · 2020

Detection methodsSpread & networks A Survey on Computational Propaganda DetectionThis survey comprehensively reviews computational propaganda detection from two complementary perspectives: text analysis (NLP) and network analysis. The authors argue that propaganda differs from misinformation/disinformation by focusing on persuasion techniques (emotional appeals, logical fallacies) rather than falsity. San Martino et al. · arXiv · 2020

Psychology & interventionsPlatforms, policy & society Inoculating Against Fake News About COVID-19COVID-19 misinformation has proliferated rapidly on social media, undermining public health responses and vaccination uptake. Rather than relying on post-hoc fact-checking (which spreads slower than misinformation), the authors propose psychological inoculation—exposing people to weakened doses of misinformation techniques beforehand to… van der Linden et al. · Frontiers in Psychology · 2020

Spread & networksPlatforms, policy & society Evaluating the fake news problem at the scale of the information ecosystemUsing nationally representative data on mobile, desktop, and TV consumption spanning 2016–2018, the authors show that fake news comprises only 0.15% of Americans' daily media diet, while TV dominates news consumption by a 5:1 ratio over online. The paper challenges the widespread narrative of fake news as a pervasive crisis and suggests… Allen et al. · Science Advances · 2020

Bots & coordinated campaignsPlatforms, policy & society Assessing the Russian Internet Research Agency's impact on the political attitudes and behaviors of American Twitter users in late 2017Combining longitudinal survey data from 1,239 partisan Twitter users with nonpublic IRA account data, Bail et al. find no evidence that interaction with Russian Internet Research Agency accounts substantially impacted six measures of political attitudes (affective/ideological polarization) or behaviors (political engagement, network… Bail et al. · National Academy of Sciences · 2020

Psychology & interventionsSpread & networks Misinformation and Morality: Encountering Fake-News Headlines Makes Them Seem Less Unethical to Publish and ShareFour preregistered experiments (N=2,587) show that repeatedly encountering fake-news headlines reduces moral condemnation of spreading them—regardless of whether people believe them. This "moral repetition effect" operates via fluency: familiar headlines feel less unethical to share, stronger inclinations to promote them online, and… Effron & Raj · Psychological Science · 2020

Bots & coordinated campaignsSpread & networks It takes a village to manipulate the media: coordinated link sharing behavior during 2018 and 2019 Italian electionsCoordinated networks of Facebook pages and groups substantially amplified problematic news during Italian elections: coordinated entities shared problematic domains 1.79×–2.22× more frequently than uncoordinated ones. The paper introduces a method to detect "coordinated inauthentic behavior" by identifying entities that… Giglietto et al. · Information, Communication & Society · 2020

Bots & coordinated campaignsPlatforms, policy & society Cross-Platform State Propaganda: Russian Trolls on Twitter and YouTube during the 2016 U.S. Presidential ElectionThis paper analyzes 1,052 Russian IRA Twitter accounts to understand their propaganda strategy during the 2016 U.S. presidential election. By examining hyperlinks to news stories and YouTube videos, the authors find IRA accounts linked to conservative sources more frequently than liberal ones, consistent with supporting Trump. Golovchenko et al. · The International Journal of Press/Politics · 2020

Psychology & interventionsPlatforms, policy & society A digital media literacy intervention increases discernment between mainstream and false news in the United States and IndiaA randomized experiment tests Facebook's "Tips to Spot False News" intervention in the US and India, finding it increases discernment between mainstream and false news (26.5% in US, 17.3% in India online). The intervention reduces belief in false headlines more than it reduces belief in mainstream ones. Guess et al. · PNAS · 2020

Fact-checking & verificationPlatforms, policy & society Fact-checking as risk communication: the multi-layered risk of misinformation in times of COVID-19COVID-19 misinformation should be viewed as a risk in its own right, not just a communication failure. Fact-checking efforts face three key challenges: defining misinformation differently across political subgroups, earning trust in an environment of low press credibility, and communicating amid genuine uncertainty. Krause et al. · Journal of Risk Research · 2020

Bots & coordinated campaignsPlatforms, policy & society Troll Factories: Manufacturing Specialized Disinformation on TwitterLinvill and Warren analyze 9.04 million tweets from Russia's Internet Research Agency (IRA) spanning 2009–2018, identifying five specialized account categories—Right Troll, Left Troll, News Feed, Hashtag Gamer, and Fearmonger—each with distinct behavioral patterns, temporal deployment strategies, and communication styles. The authors… Linvill & Warren · Political Communication · 2020

Psychology & interventionsPlatforms, policy & society Fighting COVID-19 Misinformation on Social Media: Experimental Evidence for a Scalable Accuracy-Nudge InterventionTwo pre-registered experiments with 1,700+ U.S. adults show that a simple accuracy nudge — asking people to rate the accuracy of an unrelated headline before the main task — nearly tripled their ability to discriminate true from false COVID-19 headlines when deciding what to share on social media. The intervention is scalable, requires… Pennycook et al. · Psychological Science · 2020