Modeling microscopic and macroscopic information diffusion for rumor detection
نویسندگان
چکیده
Researchers have exerted tremendous effort in designing ways to detect and identify rumors automatically. Traditional approaches focus on feature engineering, which requires extensive manual efforts are difficult generalize different domains. Recently, deep learning solutions emerged as the de facto methods online an end-to-end manner. However, they still fail fully capture dissemination patterns of rumors. In this study, we propose a novel diffusion-based rumor detection model, called Macroscopic Microscopic-aware Rumor Detection, explore full-scale diffusion information. It leverages graph neural networks learn macroscopic propagation microscopic using bidirectional recurrent while taking into account user-time series. Moreover, it knowledge distillation technique create more informative student model further improve performance. Experiments conducted two real-world data sets demonstrate that our method achieves significant accuracy improvements over state-of-the-art baseline models detection.
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ژورنال
عنوان ژورنال: International Journal of Intelligent Systems
سال: 2021
ISSN: ['1098-111X', '0884-8173']
DOI: https://doi.org/10.1002/int.22518