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| Detecting Rumor Dissemination and Sources with SIDR Model |
Chen Yixin,Chen Xinyue,Liu Yi,Wang Hanzhen,Lai Yongqing,Xu Yang( ) |
| Department of Information Management, Peking University, Beijing 100871, China |
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Abstract [Objective] This paper explores the characteristics of rumor sources and dissemination patterns, aiming to reduce their negative effects. [Methods] First, we added “fact checkers” to the traditional infectious disease model, and set changing rules for node status based on the characteristics of rumor dissemination. Then, we constructed a SIDR model with the node interaction in social networks. Third, we proposed an algorithm based on SIDR model to detect rumor sources. Finally, we optimized the proposed model with the Beam search algorithm. [Results] We examined the new model with real-world cases and found it accurately simulated the propagation of rumors. Identifying rumor sources could constrain their spread. The accuracy of our algorithm was up to 83% at the early stage.[Limitations] This paper does not consider the dynamic changes of social networks, and more representative cases should be included. [Conclusions] The proposed model could help us identify rumor sources and predict their development.
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Received: 21 July 2020
Published: 05 February 2021
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Corresponding Authors:
Xu Yang
E-mail: yang.xu@pku.edu.cn
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