Supporting Personality Estimation Based on the Percentage of Emotional Words Used in Tweets

Abstract

In recent years, social networking services (SNS) have become very popular. While it is easy to connect with many people, it is also easy to get into trouble. One of the ways to prevent troubles is to check the information of the person with whom you interact in advance. In this study, we propose a Twitter-based system that supports the selection of an interaction partner by displaying the results of personality estimation of each user based on the percentage of emotional words used in tweets. Users of this system can search for people with whom they want to interact by narrowing down the users based on the provided personality information of Twitter users and then checking the actual tweets of the narrowed users. Through experiments, we verified whether the system can smoothly find Twitter users with whom the user wants to interact.