Detection of Social Network Spam Based on Improved Machine Learning

Abstract

With the aid of several models and information, the machine learning model’s spam message identification has been carried out correctly. In order to provide accurate information and a clear understanding of the entire process, all of the prior research on the identification of spam communications inside social networking platforms was analysed. The secondary data collecting technique may assist in carrying out the research in a more suitable manner since the approach that has been employed in this study has been properly outlined with all the relevant data and references. The whole method of detecting spam messages utilizing all available machine learning models in a real-world scenario has been explained in the analysis as well as discussion part. The complete process of spam communication identification using machine learning models in a real-world situation has been explained with the aid of numerous photos from the software system and all the equations that may help to carry out the process very easily. With the aid of knowledge, many machine learning models that may be used for this goal have been properly described and discussed.