An Efficient Spam SMS Analysis Model based on Multinomial Naïve Bayes model Using Passive Aggressive Algorithm

Abstract

The social media can be a platform for information consumption nowadays. On the one hand, it's free of cost, easy access, and different data dissemination lead people to hunt out and consume social media news. On the contrary, it allows for the broad spread of "spams," i.e., inferiority news with deliberately false information. The widespread spread of spams has the potential for very negative impacts on people and society. Consequently, the detection of spam on social media has recently become an important research that draws tremendous attention. NLP, an artificial intelligence (AI) division, uses computers and human natural language to produce useful data. In text classification activities, such as spam detection and sentiment analysis, text generation, language translations and document classification, NLP is widely used.