OMT: An Operate-Based Approach for Modelling Multi-topic Influence Diffusion in Online Social Networks
- Publication Type:
- Conference Proceeding
- Citation:
- Proceedings of the 22nd International Conference on Web Information Systems Engineering (WISE), 2021, 13080 LNCS, pp. 542-556
- Issue Date:
- 2021-10-01
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| Filename | Description | Size | |||
|---|---|---|---|---|---|
| Jiang2021_Chapter_OMTAnOperate-BasedApproachForM.pdf | Published version | 1.18 MB |
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Influence diffusion modelling in online social networks has been widely studied and applied in public opinion management, viral marketing, and rumour detection. Most existing studies focus on the network topology and the complex user characteristics while ignoring the diverse topic features of the information, especially the cross-impact of multiple topics on the information propagation. In this paper, we propose the Operator-based Multi-Topic (OMT) model by considering user topic interest, topic penetration, and topic correlation to explain the topic effects on influence diffusion fully. Meanwhile, the operator-based approach inherits the advantages of the heat diffusion-based model and the agent-based model. Accordingly, the OMT is recognized as a user context-aware and topic-aware prediction model, which can improve the practicability, quality, and simulation of influence diffusion modelling in multi-topic social networks. In the experiments, real-world datasets are adopted to evaluate the performance of the proposed OMT. The experimental results demonstrate that the OMT performs effectively in diffusion simulation and influence maximization.
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