An influence maximization method based on crowd emotion under an emotion-based attribute social network
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摘要
Most research on influence maximization focuses on the network structure features of the diffusion process but lacks the consideration of multi-dimensional characteristics. This paper proposes the attributed influence maximization based on the crowd emotion, aiming to apply the user’s emotion and group features to study the influence of multi-dimensional characteristics on information propagation. To measure the interaction effects of individual emotions, we define the user emotion power and the cluster credibility, and propose a potential influence user discovery algorithm based on the emotion aggregation mechanism to locate seed candidate sets. A two-factor information propagation model is then introduced, which considers the complexity of real networks. Experiments on real-world datasets demonstrate the effectiveness of the proposed algorithm. The results outperform the heuristic methods and are almost consistent with the greedy methods yet with improved time performance.
论文关键词:Crowd emotion,Cluster credibility,Two-factor,Emotion aggregation,Influence maximization,Social networks
论文评审过程:Received 15 July 2021, Revised 3 November 2021, Accepted 8 November 2021, Available online 6 December 2021, Version of Record 6 December 2021.
论文官网地址:https://doi.org/10.1016/j.ipm.2021.102818