Detecting fake news on Chinese social media based on hybrid feature fusion method

作者：

Highlights：

• A framework FNDF extracts a total of 16 features from text, images and users respectively.

• The semantic features of text in images are deeply mined.

• Based on SiameseNet, this paper proposes a feature of image-text correlation.

• A novel deep neural network called FNN is built for hybrid feature fusion.

• The results demonstrate that our method outperforms the state-of-the-art models.

摘要

•A framework FNDF extracts a total of 16 features from text, images and users respectively.•The semantic features of text in images are deeply mined.•Based on SiameseNet, this paper proposes a feature of image-text correlation.•A novel deep neural network called FNN is built for hybrid feature fusion.•The results demonstrate that our method outperforms the state-of-the-art models.

论文关键词：Social media,Fake news,Deep learning,Image-text correlation

论文评审过程：Received 9 April 2022, Revised 1 July 2022, Accepted 6 July 2022, Available online 14 July 2022, Version of Record 18 July 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.118111