首页|False information recognition of social media platforms based on multi-modal feature fusion
False information recognition of social media platforms based on multi-modal feature fusion
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NETL
NSTL
Traditional social media platforms have low accuracy in identifying false information. Therefore, a method based on multi-modal feature fusion is proposed to recognise false information within social media platforms. This method processes false information data on social media platforms by calculating noise during transmission, and utilises multi-layer management to establish correlations between multi-modal point cloud data. By designing modal grouping and calculating similarity, we integrate information from the three dimensions of time, space, and attributes to supplement the shortcomings of the data. By utilising multi-modal feature fusion algorithms, accurate recognition of false information on social media platforms can be achieved. The experimental results show that using this method can effectively improve the training accuracy of the model and have the ability to resist false data injection attacks, achieving high recognition accuracy.
multi-modal feature fusionsocial media platformfalse informationrecognition methods
Yi Tang、Jiaojun Yi、Feigang Tan
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School of Information Technology and Engineering, Guangzhou College of Commerce
School of Economics, Guangzhou College of Commerce
School of Traffic and Environment, Shen Zhen Institute of Information Technology
NETL
NSTL
