Lei Guo*
Journal of New Media, Vol.3, No.3, pp. 99-107, 2021, DOI:10.32604/jnm.2021.019649
Abstract In recent years, with the increasing popularity of social networks,
rumors have become more common. At present, the solution to rumors in social
networks is mainly through media censorship and manual reporting, but this
method requires a lot of manpower and material resources, and the cost is
relatively high. Therefore, research on the characteristics of rumors and automatic
identification and classification of network message text is of great significance.
This paper uses the Naive Bayes algorithm combined with Laplacian smoothing to
identify rumors in social network texts. The first is to segment the text and remove
the stop words after… More >
Login
Register
