Users' Feedback on COVID-19 Lockdown Documentary: An Emotion Analysis and Topic Modeling Analysis - Shi, Xiaochuan; Jia, Miaoyutian; Li, Jia; Chen, Quiyi; Liu, Guan; Liu, Qian (Frontiers in Psychology, 2022)
Conducting emotion analysis and generating users’ feedback from social media platform could help understanding their emotional responses to videos products, such as a documentary on lockdown of Wuhan during COVID-19. The results of emotion analysis could be used to make further user recommendations for marketing purpose. In our study, we try to understand how users respond on a documentary through YouTube comments. We choose “The lockdown: One month in Wuhan” YouTube documentary, and applied emotion analysis as well as a machine learning approach on the comments. We first cleaned the data and then introduce an emotion analysis based on the statistical characteristics and lexicon combination. After that, we apply the Latent Dirichlet Allocation (LDA) topic modeling approach to further generate main topics with keywords from the comments and visualized the distribution by visualizing the topics. The result shows trust (22.8%), joy (15.4%) and anticipation (17.6%) are the most prominent emotions dominating in the comments. The major three themes accounted for 70 percent of all comments are discussing stories in fighting against the virus, medical workers are heroes and showing respect. Further discussion has been conducted on the changing of different sentiments overtime for the ongoing health crisis. This study proves that LDA topic modeling and emotion analysis could be used to generate explanations on users’ opinion and feelings to video products, which could support more effective communication or negotiation with users, or even support user recommendation in marketing.