Personality Analysis Using Classification on Turkish Tweets

Gokalp Mavis,Ismail Hakki Toroslu,Pinar Karagoz

doi:10.4018/ijcini.287596

Gokalp Mavis, Ismail Hakki Toroslu + Show 1 more

Open Access

https://doi.org/10.4018/ijcini.287596

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Abstract

According to the psychology literature, there is a strong correlation between the personality traits and the linguistic behavior of people. Due to increase in computer based communication, individuals express their personalities in written forms on social media. Hence, social media became a convenient resource to analyze the relationship between the personality traits and the lingusitic behaviour. Although there is a vast amount of studies on social media, only a small number of them focus on personality prediction. In this work, we aim to model the relationship between the social media messages of individuals and Big Five Personality Traits as a supervised learning problem. We use Twitter posts and user statistics for analysis. We investigated various approaches for user profile representation, explored several supervised learning techniques, and presented comparative analysis results. Our results confirm the findings of psychology literature, and we show that computational analysis of tweets using supervised learning methods can be used to determine the personality of individuals.

Highlights

Personality is one of the typical and enduring topics in psychology
For the second branch, firstly, important words are identified by using the Term Frequency - Inverse Document Frequency (TF-IDF) method, and they are mapped to points in high dimensional space using word embedding
We present a method for personality traits prediction by using Twitter data

Summary

Introduction

Personality is one of the typical and enduring topics in psychology. Personality prediction can be basically defined as identifying personality traits of a person by using a set of data. Social network usage is getting more and more popular and the data produced by social media users can provide a valuable resource to automatically determine human personality. Social media is one of the most commonly used services on the Internet. Studies show that one third of the time spent on Internet is allocated on social media sites (Suhartono et al, 2017). The use of social networks is increasing day by day, the number of studies focusing on the relation of social media and personality is still limited, and there are open problems to be studied such as analyzing the effective and language dependent features and the use of deep neural models for the problem (Ahmad, 2020) (Bharadwaj, 2018)

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