Automated Personality Prediction of Social Media Users: A Decade Review

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Eishita Sharma, Rhea Mahajan, Remia Mahajan, Vibhakar Mansotra

Abstract

We live in a world where social media has taken over almost every possible field and has blended into our daily lives. People like to express their interests, thoughts, and views on these social networking sites. This information reveals many psychological aspects of their behaviour that can be used to predict their personality. Personality prediction is a very comprehensive and varied field of study.Over the years, there has been an ample amount of research done in this field. In this paper, we have tried to review the work carried out for personality prediction of social media users in the past decade using the information extracted from their digital footprints. Further, we have also discussed different machine and deep algorithms, datasets, personality measures, and applications of automatic personality detection. To understand the area better, we have done a case study where we used Convolutional Neural Networks model with word embeddings to predict the personality of 50
bloggers using the data accumulated from their blog posts around various topics such as beauty, fashion, travel, food, etc.We concluded that personality of Bloggers in the real world observed in their online columns, validating the hypothesis that the nature of online interactions does not greatly differ from that of real-world interactions.

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