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Bots & coordinated campaignsDetection methods Detection of Novel Social Bots by Ensembles of Specialized ClassifiersDifferent types of social bots exhibit heterogeneous behavioral features; training a single classifier on all bots fails to generalize to novel bot types. The authors propose ESC (Ensemble of Specialized Classifiers), which trains separate classifiers for each bot class and combines their decisions via a maximum rule, achieving a 56%… Sayyadiharikandeh et al. · arXiv · 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

Datasets & evaluationDetection methods Fighting an Infodemic: COVID-19 Fake News DatasetThe authors present a manually annotated dataset of 10,700 COVID-19 related posts and articles (52% real, 48% fake) collected from social media and fact-checking websites. They benchmark four machine learning baselines (Decision Tree, Logistic Regression, SVM, Gradient Boost), achieving 93.32% F1-score with SVM, and release both the… Patwa et al. · Springer · 2020

Deepfakes & multimodalDetection methods The Creation and Detection of Deepfakes: A SurveyComprehensive 38-page survey covering both creation and detection of deepfakes. Systematically reviews generative neural network architectures (GANs, autoencoders, CNNs, RNNs), technical approaches to reenactment, replacement, editing, and synthesis. Mirsky & Lee · ACM Computing Surveys · 2020

Datasets & evaluationSpread & networks Characterizing COVID-19 Misinformation Communities Using a Novel Twitter DatasetThis paper presents CMU-MisCOV19, a manually annotated Twitter dataset of 4,573 COVID-19 tweets across 17 categories, and characterizes misinformed versus informed online communities. Key findings: misinformed communities are significantly denser (higher network density), contain more bots (19% vs 11%), and demonstrate higher… Memon & Carley · arXiv · 2020

Detection methodsDatasets & evaluation GCAN: Graph-aware Co-Attention Networks for Explainable Fake News Detection on Social MediaGCAN tackles fake news detection on Twitter with only source tweets and retweet sequences—no user comments or network structure required. The model combines graph convolution networks to capture user interactions with a dual co-attention mechanism to highlight suspicious retweeters and words. Lu & Li · arXiv · 2020

Deepfakes & multimodalDetection methods A Multi-Modal Method for Satire Detection using Textual and Visual CuesSatirical news articles are often misinterpreted as legitimate news. This work proposes a multi-modal approach using ViLBERT to detect satire by jointly analyzing headline text and thumbnail images, achieving 93.8% accuracy on a new dataset of 10,000 articles (4000 satirical, 6000 mainstream). Li et al. · arXiv · 2020

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