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Datasets & evaluationDetection methods MM-COVID: A Multilingual and Multimodal Data Repository for Combating COVID-19 DisinformationThe paper introduces MM-COVID, a multilingual and multimodal dataset of COVID-19 fake news and social engagements in six languages (English, Spanish, Portuguese, Hindi, French, Italian). The dataset includes 3,981 fake news pieces with 7,192 tweets, fact-checking metadata, user profiles, and temporal propagation information. Li et al. · arXiv · 2020

Deepfakes & multimodalDatasets & evaluation TweepFake: about detecting deepfake tweetsFirst publicly available dataset of real human-written and machine-generated tweets (TweepFake: 25,572 tweets, half human, half bot-generated from GPT-2, RNN, LSTM, Markov Chains, etc.). Benchmarks 13 detection methods and finds that transformer-based models fine-tuned on this task (RoBERTa) achieve ~90% accuracy, while BoW approaches… Fagni et al. · arXiv · 2020

Deepfakes & multimodalDatasets & evaluation The DeepFake Detection Challenge (DFDC) DatasetThis paper introduces the DFDC Dataset, the largest publicly available deepfake detection benchmark at the time with 128,154 videos from 3,426 consented actors and 100,000 face-swapped clips. The dataset addresses ethical and methodological limitations of prior deepfake benchmarks by requiring explicit participant consent, including… Dolhansky et al. · CVPR 2020 · 2020

Datasets & evaluationSpread & networks CoAID: COVID-19 Healthcare Misinformation DatasetCoAID is a benchmark dataset for COVID-19 healthcare misinformation detection comprising 4,251 news articles (204 fake, 3,565 true), 28 fake claims and 454 true claims, 296,000 user engagements from social platforms, and 926 social media posts with ground-truth labels. The dataset bridges text content, user engagement features, and… Cui & Lee · 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

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

Spread & networksDetection methods Rumor Detection on Social Media with Bi-Directional Graph Convolutional NetworksProposes Bi-GCN, a graph convolutional network approach for rumor detection that models both top-down propagation patterns (how rumors spread from source) and bottom-up dispersion patterns (how rumors diffuse within communities). By capturing both directional characteristics jointly and incorporating source post features at each layer,… Bian et al. · AAAI 2020 · 2020

Spread & networksDetection methods What Was Written vs. Who Read It: News Media Profiling Using Text Analysis and Social Media ContextThis paper predicts the political bias (left/center/right) and factuality (low/mixed/high) of news outlets by analyzing what articles they publish, who follows them on social media, and what Wikipedia says about them. The system achieves 85% accuracy on bias prediction by combining article text, YouTube video features, Twitter audience… Baly et al. · 58th Annual Meeting of the Association for… · 2020

Detection methodsDatasets & evaluation A Survey on Natural Language Processing for Fake News DetectionThis survey comprehensively reviews NLP methods for fake news detection, systematically comparing task formulations (classification vs. regression), nine benchmark datasets (LIAR, FEVER, FakeNewsNet, Twitter/SNS datasets), and five methodological approaches (preprocessing, machine learning models, rhetorical structure, evidence… Oshikawa et al. · arXiv · 2020

Deepfakes & multimodalFact-checking & verification A Picture Paints a Thousand Lies? The Effects and Mechanisms of Multimodal Disinformation and Rebuttals Disseminated via Social MediaMultimodal disinformation (paired text and images) is perceived as more credible than text-only misinformation, but fact-checkers can overcome this effect. Importantly, the modality of fact-checks (visual or textual) matters less than their presence; fact-checks are more persuasive for people whose prior attitudes already oppose the… Hameleers et al. · Political Communication · 2020

Platforms, policy & societySpread & networks Social media and vaccine hesitancyLarge-scale cross-national analysis finds that social media use to organize offline action predicts public vaccine safety skepticism, while foreign disinformation campaigns significantly reduce vaccination coverage year-over-year. A one-point increase on the five-point disinformation scale correlates with a two-percentage-point drop in… Wilson & Wiysonge · BMJ Global Health · 2020

Fact-checking & verificationPsychology & interventions Fact-Checking: A Meta-Analysis of What Works and for WhomMeta-analysis of 30 studies on fact-checking effectiveness finds modest but significant positive effects (d = 0.29) on belief correction. However, effects are substantially moderated by motivated reasoning, political ideology, message design, and context: pro-attitudinal fact-checking works better than counter-attitudinal corrections,… Walter et al. · Political Communication · 2020

Deepfakes & multimodalPlatforms, policy & society Deepfakes and Disinformation: Exploring the Impact of Synthetic Political Video on Deception, Uncertainty, and Trust in NewsExperimental study (N=2,005 UK respondents) testing how political deepfakes affect deception and trust in news. Deepfakes increased uncertainty about content, and that uncertainty mediated reduced trust in news on social media. Vaccari & Chadwick · Social Media + Society · 2020

Spread & networksPlatforms, policy & society Causes and consequences of mainstream media dissemination of fake news: literature review and synthesisWhile fake news websites have limited direct reach, mainstream media coverage is probably how most people encounter fake news stories. This synthesis identifies why mainstream outlets cover falsehoods (journalists' professional duties, news values, peer psychology, technical infrastructure) and explores how mainstream coverage amplifies… Tsfati et al. · Annals of the International Communication… · 2020

Spread & networksPlatforms, policy & society Online misinformation about climate changeComprehensive literature review examining climate change misinformation from multiple disciplinary angles. Defines misinformation vs. disinformation, identifies networks of actors (scientists, governments, industry, media) spreading false claims, examines how social media characteristics (homophily, echo chambers, algorithmic bias)… Treen et al. · WIREs Climate Change · 2020

Psychology & interventionsPlatforms, policy & society Susceptibility to misinformation about COVID-19 around the worldAn international survey of 3,750 adults across five countries (UK, Ireland, USA, Spain, Mexico) measured susceptibility to COVID-19 misinformation and examined how it predicts public health behaviors. While majorities in each country did not find COVID-19 misinformation credible, higher susceptibility to misinformation was strongly… Roozenbeek et al. · Royal Society Open Science · 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

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

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

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

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

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

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 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