Image de couverture de livre

How fake news can turn against its spreader

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Brody, Dorje C., Yuasa, Tomooki
Format:	Preprint
Publié:	2025
Sujets:	Physics and Society Information Theory Social and Information Networks
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Who should fight the spread of fake news?
par: Riazi, Diana, et autres
Publié: (2024)

Comparing the willingness to share for human-generated vs. AI-generated fake news
par: Bashardoust, Amirsiavosh, et autres
Publié: (2024)

Locating privileged spreaders on an Online Social Network
par: Borge-Holthoefer, Javier, et autres
Publié: (2011)

The voice of few, the opinions of many: evidence of social biases in Twitter COVID-19 fake news sharing
par: Castioni, Piergiorgio, et autres
Publié: (2021)

Finding Super-spreaders in Network Cascades
par: Mossel, Elchanan, et autres
Publié: (2024)

Describing the effect of influential spreaders on the different sectors of Indian market: a complex networks perspective
par: Sengupta, Anwesha, et autres
Publié: (2022)

Fake news: No ban, No spread -- with Sequestration
par: Galam, Serge
Publié: (2024)

How disinformation and fake news impact public policies?: A review of international literature
par: Silva, Ergon Cugler de Moraes, et autres
Publié: (2024)

Point process analysis of geographical diffusion of news in Argentina
par: Garcia, Lucio L., et autres
Publié: (2024)

Accurately Estimating Unreported Infections using Information Theory
par: Cui, Jiaming, et autres
Publié: (2025)

Scientific and technological knowledge grows linearly over time
par: Kang, Huquan, et autres
Publié: (2024)

Robustness of the public transport network against attacks on its routes
par: Cicchini, Tomás, et autres
Publié: (2024)

Network analysis reveals news press landscape and asymmetric user polarization
par: Lee, Byunghwee, et autres
Publié: (2024)

Finding Super-spreaders in SIS Epidemics
par: Sridhar, Anirudh, et autres
Publié: (2026)

What characteristics define disinformation and fake news?: review of taxonomies and definitions
par: Silva, Ergon Cugler de Moraes, et autres
Publié: (2024)

Three candidate election strategy
par: Brody, Dorje C., et autres
Publié: (2023)

Nonparametric inference of higher order interaction patterns in networks
par: Wegner, Anatol E., et autres
Publié: (2024)

Voter model can accurately predict individual opinions in online populations
par: Vendeville, Antoine
Publié: (2025)

Detecting fake review buyers using network structure: Direct evidence from Amazon
par: He, Sherry, et autres
Publié: (2024)

Exploring agent interaction patterns in the comment sections of fake and real news
par: Zhu, Kailun, et autres
Publié: (2024)

False memories to fake news: The evolution of the term "misinformation" in academic literature
par: Iglesias, Alejandro Javier Ruiz, et autres
Publié: (2026)

Edge interventions can mitigate demographic and prestige disparities in the Computer Science coauthorship network
par: Barnes, Kate, et autres
Publié: (2025)

What can we learn from marketing skills as a bipartite network from accredited programs?
par: Garcia-Chitiva, Maria del Pilar, et autres
Publié: (2024)

Fully personalized PageRank and algebraic methods to distribute a random walker
par: Contreras-Aso, Gonzalo, et autres
Publié: (2025)

Consistency of Maximum Likelihood for Continuous-Space Network Models I
par: Shalizi, Cosma Rohilla, et autres
Publié: (2017)

Assigning Entities to Teams as a Hypergraph Discovery Problem
par: de Arruda, Guilherme Ferraz, et autres
Publié: (2024)

How networks shape diversity for better or worse
par: Musso, Andrea, et autres
Publié: (2022)

Measuring the co-evolution of online engagement with (mis)information and its visibility at scale
par: Han, Yueting, et autres
Publié: (2025)

Political audience diversity and news reliability in algorithmic ranking
par: Bhadani, Saumya, et autres
Publié: (2020)

Unveiling the Social Fabric: A Temporal, Nation-Scale Social Network and its Characteristics
par: Cremers, Jolien, et autres
Publié: (2024)

Epidemics on the Move: How Public Transport Demand and Capacity Shape Disease Spread
par: Hajdu, László, et autres
Publié: (2025)

How Language, Culture, and Geography shape Online Dialogue: Insights from Koo
par: Mekacher, Amin, et autres
Publié: (2024)

Information Cocoons on Social Media: Why and How Should the Government Regulate Algorithms
par: Yang, Wen
Publié: (2024)

A Systematic Approach for Studying How Topological Measurements Respond to Complex Networks Modifications
par: Benatti, Alexandre, et autres
Publié: (2025)

How does node centrality in a financial network affect asset price prediction?
par: Xu, Yuhong, et autres
Publié: (2023)

The Quiet and the Compliant: How Regulation and Polarization Shape Conventional Wisdoms on Corporate Social Engagement in High-risk Settings
par: Miklian, Jason
Publié: (2026)

COVID-19 and income profile: How communities in the United States responded to mobility restrictions in the pandemic's early stages
par: Sun, Qianqian, et autres
Publié: (2020)

Dynamical evolution of social network polarization and its impact on the propagation of a virus
par: Achitouv, Ixandra, et autres
Publié: (2024)

What we can learn from TikTok through its Research API
par: Corso, Francesco, et autres
Publié: (2024)

From News Source Sharers to Post Viewers: How Topic Diversity and Conspiracy Theories Shape Engagement With Misinformation During a Health Crisis
par: Chuai, Yuwei, et autres
Publié: (2024)