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GUIDEUnderstanding fake news, misinformation & disinformation

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Spread & networksPlatforms, policy & society Why Does Misinformation Propagate Faster? An Algorithmic Perspective on XMisinformation propagates faster on X due to an "engagement fungibility mechanism" in the platform's score-aggregation layer: fast engagement signals (likes, retweets) are treated as interchangeable evidence of quality with slow signals (replies, quotes), allowing low-credibility content that draws disproportionately from instant… Li & Gao · arXiv · 2026 Bots & coordinated campaignsDatasets & evaluation Setting the clock: Evaluating temporal window parameters for coordinated behavior detectionThe paper systematically evaluates how temporal window parameters (length and stride) affect detection of coordinated communities in co-repost networks. Using 14 labeled information operation datasets, the authors find that window length is a central modeling parameter: short windows (seconds to minutes) detect tight, highly synchronized… Panayiotou et al. · AIDEM Workshop, ECML-PKDD 2026 · 2026 Psychology & interventionsSpread & networks Unifying Models of Intergroup Hostility in Online DiscourseHostile rhetoric toward outgroups in online discourse can be modeled through six mechanisms (boundary construction, threat construction, scapegoating, negative evaluation, dehumanization, action orientation) whose structural and temporal relationships were previously understood separately through competing theoretical frameworks. By… Gerard et al. · arXiv · 2026 Spread & networksPsychology & interventions How neighbourhood ideology shapes misinformation belief in densely tied social networksPrior work decouples ideological bias and social influence when modeling misinformation propagation; this paper integrates them through an agent-based contagion model that distinguishes an individual's ideological intensity from a claim's ideological alignment. Simulation and analytical results show that in densely clustered… Karimi et al. · arXiv · 2026 LLMs & generative AIPlatforms, policy & society A Multi-Stage Agentic Framework for Effective Counter-Narrative Generation and RefinementCounter-narratives are a scalable defense against misinformation and hate speech, but manual authoring is slow and labor-intensive. This paper proposes a multi-stage agent-based framework using LLMs to generate and iteratively refine counter-narratives on pro-Russian misinformation about Ukraine. Kronfeld et al. · arXiv · 2026 Platforms, policy & societySpread & networks Control-Theoretic Content ModerationContent moderation at the platform level requires balancing multiple competing objectives (reducing harmful content, preserving engagement, maintaining activity). This paper formulates platform-level moderation as a feedback control problem with a multi-objective loss function, proposes control-theoretic moderators (including… Tessa et al. · arXiv · 2026 LLMs & generative AIPlatforms, policy & society Making AI-Assisted Claims Independently Challengeable: Publication Authority and a Protocol for Falsifiable Publication RecordsAI-assisted claims can appear authoritative even when evidence, analysis, and authorization refer to different states—creating a coordination problem. This work introduces Publication Authority (PA) as a non-transferable, single-use capability governing publication transitions, and proposes PAC-2026 SF-4, an executable specification… Tiltack et al. · arXiv · 2026 Bots & coordinated campaignsSpread & networks Social bots weaken activist cohesionSocial bots during protest peaks weaken the human relational infrastructure of activism. Analyzing 2.5M tweets from the 2020 Black Lives Matter protests, the authors show that networks more exposed to bot infiltration suffered steeper declines in human cohesion (triadic closure and edge density) after the peak, with effects concentrated… Li et al. · arXiv · 2026 Spread & networksLLMs & generative AI One AI Signal, Many Human Judgments: A Bayesian Cascade Analysis of AI-based Credibility Indicators in Online Information SpreadSocial media platforms increasingly deploy AI-based credibility indicators to help users judge misinformation. This paper extends classical Bayesian cascade models to treat AI credibility signals as a shared public signal seen by all users, then derives a critical "Gateway" threshold: above it, AI predictions dominate the public record;… Lu et al. · arXiv · 2026 Detection methodsLLMs & generative AI Lazy Grounding: Attacking Search Agents with Factual EvidenceRetrieval-augmented search agents fail to robustly distinguish between evidence for the current question and evidence for semantically nearby questions. By injecting factually correct documents supporting a neighboring question into the search corpus, agents often misapply this evidence to answer the original question, achieving accuracy… Zhang et al. · arXiv · 2026 LLMs & generative AIDatasets & evaluation Counter-GEO-Bench: Evaluating Defenses Against Information-Distorting Generative Engine OptimizationAdversaries exploit Generative Engine Optimization (GEO) to craft web documents containing targeted false claims that rank highly in LLM-generated search results. This paper introduces Counter-GEO-Bench, a benchmark of 247 human-verified query-document pairs, evaluates existing guardrails (all ineffective), and proposes C-GEO Guard, a… Zheng et al. · arXiv · 2026 Spread & networksPlatforms, policy & society Quantifying Political Partisanship for Cross-Platform AnalysesPolitical partisanship measurement in social media typically relies on platform-specific features (follower networks, community structure), making cross-platform comparison difficult. This work proposes a text-based partisanship measurement method grounded in external media bias ratings, and validates it on ~1.3 million posts from… Ameen & Healey · arXiv · 2026 Spread & networksPsychology & interventions Modeling Duelling Contagions of True and False Information in the Face of Inherent Individual biasesThis paper proposes CI-SRW, an agent-based co-diffusion model integrating cognitive biases with network dynamics to explain how competing true and false information spread in social media. Using behavioral experiments and simulations, the authors find that manipulative narratives dominate when early spreaders hold them, cognitive biases… Krishna et al. · arXiv · 2026 LLMs & generative AIPlatforms, policy & society The GenAI Catch-22: Use of Generative Artificial Intelligence in Norwegian Newsrooms During the 2025 Parliamentary ElectionA longitudinal qualitative study of four major Norwegian newsrooms (NRK, TV2, VG, Dagbladet) during the 2025 parliamentary election reveals a "GenAI Catch-22": newsrooms need human expertise to oversee generative AI systems and prevent errors, but extensive use of GenAI leads to de-skilling that erodes that very expertise, rendering… Reisjå & Løvtie · arXiv · 2026 LLMs & generative AIDetection methods Industrialized Deception: The Collateral Effects of LLM-Generated Misinformation on Digital EcosystemsThis paper updates the state of generative AI and misinformation research since 2024, documenting the shift toward industrialized deception through improved LLMs and multimodal systems. The authors present two methodological tools—JudgeGPT (for measuring human perception of AI-generated content) and RogueGPT (for controlled stimulus… Loth et al. · ACM Web Conference 2026 · 2026 LLMs & generative AIDatasets & evaluation Beyond Speculation: Measuring the Growing Presence of LLM-Generated Texts in Multilingual DisinformationThis empirical study provides the first measurement of LLM-generated content in real-world disinformation datasets. Analyzing the MultiClaim dataset (fact-checked social media posts), the authors document a 99% increase in machine-generated content from 2021 to 2023 (0.93% to 1.85%), correlating with ChatGPT's November 2022 release. Macko et al. · IEEE Computer · 2026 Psychology & interventionsDetection methods Why People Believe Misinformation — and What We Can Do About ItJon Roozenbeek synthesizes eight years of misinformation research, examining why people believe false information and what interventions actually work. Grounding the analysis in the historical tobacco disinformation playbook, he argues that misinformation susceptibility stems not primarily from poor reasoning, but from media consumption… Roozenbeek · Webimmunization Project · 2025 Psychology & interventionsFact-checking & verification Psychological Inoculation Against MisinformationSander van der Linden surveys the psychology of misinformation susceptibility and defends the approach of psychological inoculation (pre-bunking) over fact-checking (debunking). He introduces the MIST (Misinformation Susceptibility Test), a psychometrically validated instrument for measuring individual variation in susceptibility to… van der Linden · 2025 Deepfakes & multimodalDatasets & evaluation VLDBench: Evaluating Multimodal Disinformation with Regulatory AlignmentVLDBench is the first large-scale human-verified benchmark for multimodal disinformation detection, comprising 31,339 news articles paired with images across 13 topical categories. Evaluation of 9 LLMs and 10 VLMs shows vision-language models substantially outperform text-only baselines (e.g., LLaMA-3.2-11B-Vision: 74.82% accuracy), but… Raza et al. · arXiv · 2025 LLMs & generative AIDetection methods Challenges and Innovations in LLM-Powered Fake News Detection: A Synthesis of Approaches and Future DirectionsThis survey synthesizes recent advances in applying large language models to fake news detection on social media. The review covers four major LLM-based frameworks (MiLk-FD, FND-LLM, DAFND, SheepDog), identifies critical challenges around multimodal integration, adversarial robustness, scalability, and interpretability, and proposes… Yi et al. · arXiv · 2025 LLMs & generative AIDetection methods SINcon: Mitigate LLM-Generated Malicious Message Injection Attack for Rumor DetectionMessage Propagation Tree (MPT) based rumor detection models are vulnerable to LLM-generated malicious message injection attacks that alter tree topology and semantics. The paper proposes SINcon, a contrastive learning defense that regularizes models to assign similar predictive influence to nodes of different importance levels,… Zhang et al. · arXiv · 2025 Detection methodsLLMs & generative AI Propasafe: A BERT-based offline tool for propaganda detectionOriginal privacy-focused, offline browser extension using fine-tuned BERT on the Propaganda Techniques Corpus for sentence-level propaganda classification. No online inference required; binary classification (propaganda or non-propaganda). Sharma et al. · ACM Web Conference 2025 · 2025 Psychology & interventionsDetection methods The Science of MisinformationVan Bavel synthesizes research on misinformation psychology, spread mechanisms, and evidence-based interventions. Misinformation is a persistent global risk (World Economic Forum priority). Van Bavel · 2024 LLMs & generative AIPlatforms, policy & society Controlled Change(Stub page — referenced in context of GenAI adoption in journalism. To be expanded with full paper details.) Dodds · 2024