Abstract
The spread of rumor in online network results in undesirable social effects and even leads to economic losses. To overcome this problem, a lot of work studies the problem of rumor control which aims at limiting the spread of rumor. Unfortunately, all previous work only assumes that users are passive receivers of rumors even if the users can browse the rumors on their own, or the cost of the ‘anti-rumor’ node is uniform although it is impossible that the price of broadcasting information on Baidu’s homepage is the same as personal homepage’s. Considering the above problems, in this paper, we study the Rumor Control within Budget Constraint (RCBC) problem. Given a node-weighted graph G(V, E) and a budget B, it aims to find a protector set P, which can minimize the spread of rumor set R in the online network, and the total cost of node in \({P}\) does not exceed budget B. In consideration of the rumor spread via users’ browsing behaviors, we model the rumor propagation based on the random walk model. To solve this problem efficiently, we propose two greedy algorithms that can approximate RCBC within a ratio of \(\frac{1}{2}(1 - 1/e)\). To improve the efficiency of them further, we devise a PreSample method to eliminate nodes that can’t access \({R}\) by T-length random walk. Experiments on real datasets have been conducted to verify the efficiency, effectiveness, memory consumption and scalability of our methods.
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Acknowledgements
This work is supported by the National Key Research and Development Program of China (Project Number: 2018YFB1003400) and the Fundamental Research Funds for the Central Universities (Project Number: 2042017kf1017).
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Mo, S., Tian, S., Wang, L., Peng, Z. (2019). Minimizing the Spread of Rumor Within Budget Constraint in Online Network. In: Sun, X., He, K., Chen, X. (eds) Theoretical Computer Science. NCTCS 2019. Communications in Computer and Information Science, vol 1069. Springer, Singapore. https://doi.org/10.1007/978-981-15-0105-0_9
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