A Spam Detection Mechamism in Social Media using Soft Computing

Social media is gaining its popularity with growing pace. It is used for sharing information, photos, videos and other useful content in form of messages, reviews, tweets, comments etc.. More than useful information, these messages contained fraudulent content, malicious links, viruses, harassing reviews etc. These activities are increasing in numbers by spammers also called as spam users. They usually create fake profiles which look attractive to legitimate users. So, the detection of spam has become an important requirement now-a-days. An approach is used in the proposed work to detect spam using fuzzy logic and analyze through neural network multilayer perceptron. The motive behind using this approach is to learn and apply the machine learning algorithms, fuzzy logic, and (or) artificial intelligence. Also, it aimed to overcome the limitations of supervised learning algorithm by using semi - supervised approach. It has been found that the fuzzy logic applied has handled the large data set efficiently and consumed less time to detect the spammers within seconds. Thus, reducing the cost, time and need of complex software