EXPLORING OF MACHINE LEARNING ALGORITHMS FOR PERSONALITY PREDICTION OVER SOCIAL MEDIA

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P Sowmya, (M.Tech), N Sai Lohitha, M.Tech(Ph.D) , V Saraswati Bai, M.Tech(Ph.D)

Abstract

Social Media is the best example of the advancement of technology. Personality prediction is used to define the personalities of users on the basis of their online activities. These strategies may vary with machine learning techniques, various data source materials, and multiple data sets. This paper aims to identify and to predict the characteristics of social media users depending on the various features and measures of 5 personality models. The results are predicted based on analyzing the various frameworks of online communities and grammatical structures like tweets, posts, and profile information and status related to personality interactions. This can be predicted firstly, by analyzing and understanding the relationship between users and behavior interactions between them. Secondly, identify the higher potential network feature by different machine learning algorithms and define the relationship between the different dictionaries and feature sets and data sets. With the help of numerous machine learning algorithms such as Regression Analysis, Gradient Boosting, Support Vector Machine, and Neural Networks algorithms and distinct machine learning approaches, analyze the correlation and similarity across each data set and personality traits. Therefore the outcome of the accurate personality prediction shows that the different personalities under the data set have been tested. The best performance will be achieved by understanding the specific Social Network Analysis (SNA) and SPLICE, LIWC proposed in the feature extraction, which helps to predict high-precision personalities

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