An influence maximization method based on crowd emotion under an emotion-based attribute social network

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 gr...

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Bibliographic Details
Published in:Information processing & management 2022-03, Vol.59 (2), p.102818, Article 102818
Main Authors: Li, Weimin, Li, Yaqiong, Liu, Wei, Wang, Can
Format: Article
Language:English
Subjects:
Algorithms
Cluster credibility
Crowd emotion
Datasets
Emotion aggregation
Emotions
Heuristic methods
Influence maximization
Information dissemination
Maximization
Optimization
Social networks
Two-factor
User behavior
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Summary: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.
ISSN:0306-4573
1873-5371
DOI:10.1016/j.ipm.2021.102818