Misinformation due to asymmetric information sharing
Dados Bibliográficos
| ID | 7523216 |
|---|---|
| Autores | Berno Buechel (0000-0001-8709-7877, University of Fribourg, autor correspondente), Stefan Klößner (0000-0002-6558-7370, University of Vechta), Fanyuan Meng (0000-0002-7825-8509, University of Fribourg), Anis Nassar (University of Fribourg) |
| Ano | 2023 |
| Volume | 150 |
| Páginas | 104641-104641 |
| Data de publicação | 2023-04-01 |
| Peer Reviewed | Sim |
| Open Access | Sim |
| Tipo | ARTICLE |
| Periódico | Journal of Economic Dynamics and Control (JOURNAL) |
| Identificadores do periódico | ISSN: 0165-1889 • E-ISSN: 1879-1743 |
| Editora | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.jedc.2023.104641 |
| OpenAlex | W4362509376 |
| Idioma | EN |
| Citações recebidas | 3 |
| Referências citadas | 42 |
On social media platforms, true and false information compete. Importantly, some messages travel much further than others, even if they concern the same topic. This fact is not reflected in models of social learning (or opinion formation) in networks. Our model fills this gap by allowing different types of information to have different decay factors and to be shared with different networks of people, incorporating asymmetries in sharing behaviors. More “shareable” information then dominates in the long run. This yields a substantial probability of misinformation, in contrast to the special case of symmetry covered by the literature. Asymptotic learning requires a perfect balance between two types of asymmetry: the product of decay factor and largest eigenvalue in the respective signal sharing networks must coincide. Approaching this balance reduces the speed of convergence and enables social learning in the shorter term. Our analysis thus suggests that policy makers, who do not know the true state, aim to mitigate asymmetries in signal sharing, e.g. by weakening echo chambers or by fostering the shareability of cumbersome, boring messages
Asymmetry · Balance (ability · Business · Computer security · Economics · Information asymmetry · Information sharing · Internet privacy · Knowledge management · Microeconomics · Misinformation · Physics · Product (mathematics · Social learning · Social media · World Wide Web · Complex Network Analysis Techniques · Computer Science · Mathematics · Misinformation and Its Impacts · Opinion Dynamics and Social Influence · Psychology
Reaching a Consensus
The Structural Virality of Online Diffusion
The online competition between pro- and anti-vaccination views
Spread of (mis)information in social networks
A Theory of Non-Bayesian Social Learning
Non-Bayesian Social Learning and the Spread of Misinformation in Networks
Testing Models of Social Learning on Networks
Non-Bayesian social learning
Learning in Social Networks
Confirmation Bias in Social Networks
Research note
Factoring and weighting approaches to status scores and clique identification
Social influence and opinions
How Homophily Affects the Speed of Learning and Best-Response Dynamics
Persuasion Bias, Social Influence, and Unidimensional Opinions
Opinion dynamics and wisdom under conformity
A model of anonymous influence with anti-conformist agents
Does Media Literacy Help Identification of Fake News? Information Literacy Helps, but Other Literacies Don't
Theoretical Foundations for Centrality Measures
Power and Centrality
| Obras citantes distintas | 3 |
|---|---|
| Citações por ano | 0,43 |
| Intervalo de citações | 2019 - 2024 (6) |
| Velocidade de citação | recent |
| Altamente citado | Não |
| Tipos de citação | Neutras: 3 |