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Spread & networksDatasets & evaluation Prevalence of Health Misinformation on Social Media: Systematic ReviewSystematic review of 69 studies examining health misinformation prevalence across social media platforms. Vaccines, drugs, and smoking are the most-studied topics; Twitter is the primary platform for misinformation about smoking and substances, while vaccines are discussed broadly across platforms. Suarez-Lledo & Alvarez-Galvez · Journal of Medical Internet Research · 2021 Spread & networksDatasets & evaluation A Survey of Information Cascade Analysis: Models, Predictions, and Recent AdvancesThis comprehensive survey systematizes research on predicting information cascade growth and structure across social networks, covering feature-based models, generative models, and deep learning approaches. It provides a taxonomy of prediction methods across temporal, structural, user/item, and content features; evaluation metrics and… Zhou et al. · ACM Computing Surveys · 2021 Spread & networksPlatforms, policy & society Prevalence of Health Misinformation on Social Media: Systematic ReviewThis systematic review of 69 studies characterizes health misinformation topics and their prevalence across social media platforms. Health misinformation was most prevalent on Twitter regarding smoking and drugs; vaccines, noncommunicable diseases, and pandemics were also common topics. Suarez-Lledo & Alvarez-Galvez · Journal of Medical Internet Research · 2021 Spread & networksPsychology & interventions The Gospel According to Q: Understanding the QAnon Conspiracy from the Perspective of Canonical InformationThis paper systematically studies the QAnon conspiracy theory by collecting and analyzing 4,961 unique Q drops from six aggregation sites. The authors find that aggregation sites show poor agreement on what constitutes a canonical Q drop, that Q drops are incoherent and low-quality relative to other social media platforms, and that… Papasavva et al. · 16th International AAAI Conference on Web and… · 2021 Detection methodsSpread & networks User Preference-aware Fake News DetectionProposes UPFD, which detects fake news by jointly modeling user endogenous preferences (from historical posts) and exogenous context (news propagation graphs) via GNNs. Shows confirmation bias drives news sharing decisions, and historical user behavior provides complementary signals to improve detection over content-only and graph-only… Dou et al. · SIGIR 2021 · 2021 Spread & networksDetection methods Causal Understanding of Fake News Dissemination on Social MediaThe paper addresses the fundamental causal question: what user attributes cause susceptibility to share fake news? Rather than observing correlations, the authors use inverse propensity scoring (IPS) to learn unbiased embeddings of fake news sharing behavior, treating these embeddings as confounders in a causal model. Cheng et al. · ACM SIGKDD Conference on Knowledge Discovery… · 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 Spread & networksPsychology & interventions Shared partisanship dramatically increases social tie formation in a Twitter field experimentA Twitter field experiment with bot accounts reveals that shared partisanship causally drives social tie formation: users were nearly three times more likely to reciprocally follow accounts matching their political party, regardless of the account's partisan intensity. Critically, this preference was symmetric—Democrats and Republicans… Mosleh et al. · National Academy of Sciences · 2021 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 Spread & networksPlatforms, policy & society Examining the consumption of radical content on YouTubeLarge-scale study of 309,813 U.S. users' YouTube and web browsing from 2016–2019 finds that news consumption on YouTube is dominated by mainstream, centrist sources. While far-right content exists and engages users intensely, it remains a small and stable share. Hosseinmardi et al. · PNAS · 2021 Spread & networksPlatforms, policy & society The echo chamber effect on social mediaComparative analysis of 100+ million posts across Twitter, Facebook, Reddit, and Gab on controversial topics shows echo chambers operate differently by platform: Facebook and Twitter exhibit strong homophilic clustering and polarized information diffusion, while Reddit and Gab show single-sided communities without the biased diffusion… Cinelli et al. · National Academy of Sciences · 2021