A Microblog Rumor Detection Model Incorporating Multivariate Features
DOI:
https://doi.org/10.54097/cpl.v11i2.12814Keywords:
Weibo Rumors; Feature Fusion; Deep Learning.Abstract
The wide spread of microblog rumors has seriously disturbed the network public order and greatly affected people's lives. The traditional microblog rumor detection model only focuses on semantic information and has insufficient generalization ability. Aiming at this problem, this study constructs a novel microblog rumor detection model by using rumor propagation pattern features and rumor propagation user features, combined with semantic information. The experimental results show that the model achieves an accuracy of 96.3% on the microblog rumor public dataset, and all other evaluation indexes also perform well.
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