A Method for Identifying Personality Traits in Telegram

Abstract

Accessing people’s personality traits has always been a challenging task. On the other hand, acquiring personality traits based on behavioral data is one of the growing interests of human beings. Numerous researches showed that people spend a lot of time on social networks and show behaviors that create some personality patterns in cyberspace. One of these social networks that have been widely welcomed in some countries, including Iran, is Telegram. The basis of this research is automatically identifying users’ personalities based on their behavior on Telegram. For this purpose, messages from Telegram group users are collected, and then the personality traits of each member according to the famous NEO Personality Inventory (NEO PI-R) are identified. For personality analysis, the study employed three methods, including; Cosine Similarity, Bayes, and MLP algorithms.