Application of Machine Learning in the Social Network

This chapter provides a survey of different metaheuristic machine learning algorithms used for various interesting research problems in the domain of social networks and big data. It illustrates the flow of content from social media to a big data storage system and the analysis by machine learning and natural language processing. The chapter discusses the regression-based concepts and their application in social networks. It illustrates several applications, such as spam content classification, labeling data available in an online social network, medical data classification, human behavior analysis, and sentiment analysis. Sentiment analysis classifies the users’ emotions from the text they share on social media and microblogging sites. The chapter provides a few examples where deep learning and evolutionary computing have been used to solve research issues in social networks. Community detection is one of the most important problems of social networks where evolutionary algorithms have been effectively used.

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