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Spread & networksPlatforms, policy & society
Social Media and Fake News in the 2016 ElectionAllcott and Gentzkov provide the first comprehensive empirical evidence on fake news exposure during the 2016 US election. Drawing on a curated database of 156 fake news articles, web traffic data, and a post-election survey of 1,200 adults, they estimate the average American saw and remembered 1.14 fake news articles during the election…
Spread & networksPsychology & interventions
Filter Bubbles, Echo Chambers, and Online News ConsumptionThis paper examines whether technological changes (social media, search engines) increase ideological segregation in online news consumption by analyzing web-browsing data from 50,000 active news readers. They find that while social media and search are associated with higher segregation than direct browsing, the overall effects are…
Spread & networksPlatforms, policy & society
Reducing Controversy by Connecting Opposing ViewsThis paper proposes an algorithmic approach to reduce polarization on social media by recommending social connections (edges) between opposing sides. Using an endorsement graph representation and the random-walk-based controversy metric, the authors formulate the problem as k-edge-addition and develop an efficient algorithm (ROV) that…
Spread & networksPlatforms, policy & society
Corporate funding and ideological polarization about climate changeFarrell analyzes 40,785 texts (39+ million words) from 164 climate contrarian organizations between 1993–2013, employing Structural Topic Modeling and social network analysis to demonstrate that corporate funding from entities like ExxonMobil and Koch family foundations directly influences which polarization themes are created and…
Spread & networksDatasets & evaluation
Rumor CascadesFriggeri et al. tracked thousands of rumors on Facebook using Snopes.com as ground truth, finding that rumor cascades run deeper in the social network than typical content. True rumors spread more virally than false ones despite false rumors being more frequently uploaded; Snopes fact-checks increase deletion likelihood for false rumors…
Spread & networksDetection methods
Can Cascades be Predicted?Information cascades on social networks can be predicted with reasonable accuracy (~80%) using temporal and structural features extracted from early observations. Performance improves substantially as more cascade stages are observed.
Detection methodsSpread & networks
Information Credibility on TwitterThis paper proposes supervised learning classifiers to automatically assess the credibility of news discussed on Twitter. Using human-labeled topics from trending discussions, the authors extract message-level, user-level, topic-level, and propagation-level features to build classifiers that distinguish newsworthy from conversational…
Spread & networksDatasets & evaluation
The structure and function of complex networksThis comprehensive review surveys the properties and mathematical models of complex networks across diverse domains: social networks, the Internet, biological networks, and collaboration networks. Newman covers observed structural properties (degree distributions, clustering, small-world effects), foundational models (random graphs,…
Spread & networksPsychology & interventions
A Theory of Fads, Fashion, Custom, and Cultural Change as Informational CascadesFoundational theoretical framework explaining how fads, fashions, and beliefs spread through sequential information cascades: when individuals use others' actions to infer information while ignoring their own private signals, widespread adoption of incorrect beliefs and practices can occur.