Mitigating Misinformation Spread in Blockchain-Based Online Social Networks
Dados Bibliográficos
| ID | 22108398 |
|---|---|
| Autores | Rui Luo (0000-0003-0711-8039, City University of Hong Kong), Vikram Krishnamurthy (0000-0002-4170-6056, Cornell University) |
| Ano | 2026 |
| Volume | 13 |
| Fascículo | 1 |
| Páginas | 817-828 |
| Data de publicação | 2026-02-01 |
| Open Access | Sim |
| Tipo | ARTICLE |
| Periódico | IEEE Transactions on Computational Social Systems (JOURNAL) |
| Identificadores do periódico | ISSN: 2329-924X • E-ISSN: 2373-7476 |
| Editora | Institute of Electrical and Electronics Engineers (IEEE) (PUBLISHER) |
| DOI | 10.1109/tcss.2025.3598599 |
| OpenAlex | W4415482559 |
| Idioma | EN |
| Referências citadas | 38 |
This article designs a blockchain protocol to mitigate the spread of misinformation in online social networks. The blockchain protocol processes social media postings as transactions, with misinformation being treated as double-spend attacks. The probability and duration for a double-spend attack to succeed within the blockchain protocol are used to compute the misinformation propagation time distribution. Our findings indicate that the rate of misinformation propagation in blockchain-based online social networks is inversely correlated with the fraction of honest miners who reject double-spend attacks. To further analyze the dynamics of misinformation propagation, we employ a susceptible–infectious–recovered (SIR) model combined with preferential attachment in a multicommunity network, which accounts for homophily and community structure in social networks. Numerical experiments using parameters estimated from real-world Twitter hashtag datasets show that the proposed blockchain protocol can reduce the number of users exposed to misinformation by delaying its propagation
Homophily · Misinformation · Social media · Blockchain Technology Applications and Security · Misinformation and Its Impacts · Spam and Phishing Detection
Misinformation in and about science
Statistical mechanics of complex networks
Virality Prediction and Community Structure in Social Networks
The rise of social bots
Fréchet-Statistics-Based Change Point Detection in Dynamic Social Networks
Echo Chambers and Segregation in Social Networks
Perceptions of mis- or disinformation exposure predict political cynicism
Birds of a Feather
| Altamente citado | Não |
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