A Review of Extracting and Mining User Interest from Social Media Based on Personality

Abstract

Social platforms such as Facebook, Twitter, Instagram, and YouTube have escalated the content published over the internet by the users. Such platforms are considered salient influencing the daily activities causing the various segmentations in the society. The availability of user-generated social media content offers the opportunity to create models capable of extracting and predicting user interests efficiently. Many literature studies attempt the extract user interests to obtain the linage and the co-relation between individuals. However, extracting implicit and future user interests is challenging in research. Therefore, the purpose of this paper is to review the existing methods, the efficiency of extracting and predicting user interests, and to highlight the limitations of the existing methods and techniques. This paper can be beneficial to many research and postgraduate students who focus on the topic related to user personality categorization and, text mining over social media.