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Detection methodsDatasets & evaluation
Detection and Resolution of Rumours in Social Media: A SurveyComprehensive survey of rumour detection and resolution in social media covering the entire pipeline: rumour definition and characterization, data collection strategies, annotation schemes, detection approaches for both emerging and long-standing rumours, tracking of rumour propagation, stance classification (support/deny/query/comment),…
Fact-checking & verificationDatasets & evaluation
The Fact Extraction and VERification (FEVER) Shared TaskThis paper presents results of the first FEVER shared task competition, which challenged 23 teams to classify whether human-written factoid claims could be SUPPORTED or REFUTED using evidence retrieved from Wikipedia. The best system achieved 64.21% FEVER score, demonstrating the difficulty of joint evidence retrieval and natural…
Platforms, policy & societyFact-checking & verification
The Science of Fake NewsThis multidisciplinary review establishes a scientific framework for studying fake news, defining it as fabricated information that mimics news media form but lacks editorial norms. The paper identifies two mitigation strategies—empowering individuals through fact-checking and education, and structural platform interventions—while…
Fact-checking & verificationDatasets & evaluation
ClaimBuster: The first end-to-end fact-checking systemFoundational work introducing ClaimBuster, an end-to-end automated fact-checking system. Introduces a dataset of 23,533 human-annotated U.S. debate statements with check-worthiness labels, establishing baselines for automated claim check-worthiness detection and ranking.
Fact-checking & verificationPsychology & interventions
Claim Ranking in Political DebatesEarly work framing check-worthiness as claim ranking; introduces the notion of "importance weighting" for prioritizing claims for fact-checking in political debates. Foundational for understanding which claims warrant verification effort.
Detection methodsFact-checking & verification
Truth of Varying Shades: Analyzing Language in Fake News and Political Fact-CheckingThis paper performs a linguistic analysis of fake news across four categories—satire, hoaxes, propaganda, and trusted news—using lexical features (LIWC, subjectivity, hedging, intensifiers). Experiments show that fake news articles use more first-person pronouns, exaggerative language (superlatives, modal adverbs), and hedging, while…
Spread & networksDatasets & evaluation
SemEval-2017 Task 8: RumourEval: Determining rumour veracity and support for rumoursRumourEval is a shared task benchmark for detecting and verifying rumours in social media. It introduces two subtasks: (a) stance classification (SDQC: Support/Deny/Query/Comment) of replies to rumourous claims, and (b) veracity prediction (true/false) of source tweets.
Psychology & interventionsPlatforms, policy & society
Inoculating the Public against Misinformation about Climate ChangeLarge-scale experiments (N=2,167) demonstrate that misinformation about scientific consensus on climate change nullifies the effect of consensus messaging. Pre-emptive inoculation—warning people about misleading tactics and providing refutations—preserves two-thirds of the consensus effect.
Platforms, policy & societyFact-checking & verification
Defining "Fake News": A typology of scholarly definitionsThis paper reviews 34 academic studies (2003–2017) that use the term "fake news" and proposes a unified typology based on two dimensions: level of facticity (reliance on facts) and author's intention to deceive. The typology identifies six distinct types—satire, parody, fabrication, manipulation, advertising, and propaganda—clarifying…
Psychology & interventionsPlatforms, policy & society
Neutralizing misinformation through inoculation: Exposing misleading argumentation techniques reduces their influencePre-emptively exposing people to flawed arguments before they encounter misinformation (inoculation) reduces that misinformation's influence. Two experiments tested this on climate change: false-balance media coverage (equal weight to consensus vs. contrarian scientists) and fake-expert arguments (using unqualified scientists to…
Datasets & evaluationFact-checking & verification
Are You a Racist or Am I Seeing Things? Annotator Influence on Hate Speech Detection on TwitterThis paper compares hate speech detection systems trained on expert annotations (from feminist and anti-racism activists) versus amateur annotations (crowdsourced via CrowdFlower) on 6,909 tweets. Systems trained on expert annotations significantly outperform those trained on amateur data, and amateur annotators systematically label more…
Fact-checking & verificationPlatforms, policy & society
Boundaries Not Drawn: Mapping the institutional roots of the global fact-checking movementGraves maps the institutional landscape of 64+ fact-checking organizations globally across two summits (2014–2015), using ethnographic fieldwork and ternary plots to sort organizations along three axes: journalism, academia, and politics/civil society. The movement has a journalistic core but exhibits striking institutional diversity and…
Platforms, policy & societyPsychology & interventions
In Related News, That Was Wrong: The Correction of Misinformation Through Related Stories Functionality in Social MediaThis study tests whether Facebook's "related stories" feature can correct misinformation by exposing users to debunking information. Two experiments (students and Mechanical Turk workers) examined vaccine-autism and GMO-illness misperceptions.
Detection methodsFact-checking & verification
Fact Checking: Task definition and dataset constructionThis paper introduces fact-checking as a formal computational task: assessing the truthfulness of political claims as an ordinal classification problem with five labels (TRUE, MOSTLYTRUE, HALFTRUE, MOSTLYFALSE, FALSE). The authors construct a dataset of 106 objectively-verifiable fact-checked statements from PolitiFact and Channel 4 (out…
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…
Psychology & interventionsFact-checking & verification
Misinformation and Its Correction: Continued Influence and Successful DebiasingThis comprehensive review synthesizes literature on why false beliefs persist despite corrections, examining cognitive mechanisms (coherence, credibility, source confusion, fluency) that render misinformation resistant to change. The authors propose evidence-based debiasing strategies—warnings, alternative explanations, repeated…