A Comparative Study of Estimation of Video Viewer Emotion Using YouTube Video Comments

YouTube is a online video sharing service that is that many people view. If we can know the emotions of video viewers, we can use them to improve usability. In this study, we propose two method for estimating the emotion of YouTube videos from the comments of each video: a BERT-based method and a rule-based method. For the former, we use BERT with fine-turning by 350 video comments to estimate the emotion. In the rule-based method, emotion values are calculated using a Japanese emotional expression dictionary. To evaluate these methods, we obtained emotion values from 100 respondents who were asked to fill out questionnaires as ground truth. The results of the evaluation using cosine similarity showed that BERT-method was able to estimate emotions with higher accuracy than the rule-based method.