Abstract
In order to avoid the release and dissemination of eroticism, gamble, drug and politically sensitive message in social network, and purify the network space, we propose a method to detect unhealthy message in social network. Firstly, the Naive Bayes model is used to classify the message released by the social network. Then, according to the features of all kinds of unhealthy message, the classification model of Support Vector Machine (SVM) is used to make further judgment. The comparative experiment results show that, the classification model of SVM has better precognitive effect than that of Naive Bayes and Decision Tree.
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Acknowledgement
This work was supported by the National Natural Science Foundation of China Nos. 61672101, the Beijing Key Laboratory of Internet Culture and Digital Dissemination Research (ICDDXN004)* and Key Lab of Information Network Security, Ministry of Public Security, No.C18601.
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Xu, Y., Jiao, Y., Chen, S., Li, Y. (2019). Research on Detection Method of Unhealthy Message in Social Network. In: Sun, X., Pan, Z., Bertino, E. (eds) Artificial Intelligence and Security. ICAIS 2019. Lecture Notes in Computer Science(), vol 11632. Springer, Cham. https://doi.org/10.1007/978-3-030-24274-9_45
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DOI: https://doi.org/10.1007/978-3-030-24274-9_45
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