Investigating the structure of emotions by analyzing similarity and association of emotion words

TL;DR

This study examined the validity of Plutchik's wheel of emotion by analyzing semantic networks of emotion words, revealing overall similarity but local differences in structure.

Contribution

It created and analyzed semantic networks of emotion words to empirically evaluate the structure proposed by Plutchik's wheel of emotion.

Findings

Networks mostly aligned with the wheel of emotion

Local differences found in network structures

Community detection revealed nuanced emotion groupings

Abstract

In the field of natural language processing, some studies have attempted sentiment analysis on text by handling emotions as explanatory or response variables. One of the most popular emotion models used in this context is the wheel of emotion proposed by Plutchik. This model schematizes human emotions in a circular structure, and represents them in two or three dimensions. However, the validity of Plutchik's wheel of emotion has not been sufficiently examined. This study investigated the validity of the wheel by creating and analyzing a semantic networks of emotion words. Through our experiments, we collected data of similarity and association of ordered pairs of emotion words, and constructed networks using these data. We then analyzed the structure of the networks through community detection, and compared it with that of the wheel of emotion. The results showed that each network's structure was, for the most part, similar to that of the wheel of emotion, but locally different.