Mitigating Misinformation Spread in Blockchain-Based Online Social Networks

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.

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Publication Details

Journal
IEEE Transactions on Computational Social Systems
Published
2025-10-23
DOI
https://doi.org/10.1109/tcss.2025.3598599
Primary Topic
Spam and Phishing Detection
Type
article
Field-Weighted Citation Impact
0.00

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article

Mitigating Misinformation Spread in Blockchain-Based Online Social Networks

Vikram Krishnamurthy, Rui Luo
IEEE Transactions on Computational Social Systems
Spam and Phishing Detection
article

Mitigating Misinformation Spread in Blockchain-Based Online Social Networks

Vikram Krishnamurthy, Rui Luo
article en

Abstract

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.

IEEE Transactions on Computational Social SystemsVol. 13(1)
City University of Hong Kong (HK), Cornell University (US)
National Science Foundation, City University of Hong Kong, U.S. Air Force, Army Research Office
Openalex Percentile: Top 56%
Spam and Phishing Detection
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