Weibo Rumor Detection Method Based on User and Content Relationship

Autor: Hai-Jun Zhang, Wei-Min Pan, Zhong-Yue Zhou
Rok vydání: 2020
Předmět:
Zdroj: Lecture Notes in Electrical Engineering ISBN: 9789811501869
DOI: 10.1007/978-981-15-0187-6_51
Popis: In order to effectively identify the rumor information in the Weibo platform, we propose a combined model based on deep learning, which includes convolutional neural network (CNN) that incorporates the attention mechanism and combines with the neural network of long short-term memory (LSTM) to implement a microblog rumor detection method for the characteristics of user-content relations. Firstly, the convolutional neural network incorporating the attention mechanism is used to extract the fine-grained features of the user-content relationship. Secondly, the LSTM network is used for coarse-grained feature extraction. Finally, the extracted feature vectors are classified by the Softmax classifier so as to achieve a good effect of rumor detection.
Databáze: OpenAIRE