Wen Jiang1,2, Mingshu Zhang1,2,*, Xu'an Wang1,3, Wei Bin1,2, Xiong Zhang1,2, Kelan Ren1,2, Facheng Yan1,2
CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2161-2179, 2024, DOI:10.32604/cmc.2024.053762
Abstract With the rapid spread of Internet information and the spread of fake news, the detection of fake news becomes more and more important. Traditional detection methods often rely on a single emotional or semantic feature to identify fake news, but these methods have limitations when dealing with news in specific domains. In order to solve the problem of weak feature correlation between data from different domains, a model for detecting fake news by integrating domain-specific emotional and semantic features is proposed. This method makes full use of the attention mechanism, grasps the correlation between different… More >
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