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.

翻译：在自然语言处理领域，部分研究尝试通过将情感作为解释变量或响应变量来处理文本情感分析。在此背景下最常用的情感模型之一是Plutchik提出的情感轮。该模型将人类情感以环形结构进行图示化，并在二维或三维空间中加以表征。然而，Plutchik情感轮的有效性尚未得到充分验证。本研究通过构建和分析情感词汇的语义网络来检验情感轮的有效性。实验中，我们收集了有序情感词对的相似性与关联性数据，并利用这些数据构建网络。随后通过社区检测方法分析网络结构，并将其与情感轮的结构进行比较。结果表明，各网络结构在整体上与情感轮结构相似，但在局部存在差异。