An Analysis of YouTube Commenters’ Sentiments toward Transgender Individuals Using NLP
Keywords:
audience research, transgender, sentiments, natural language processing, YouTubeAbstract
This study explores the relationship between gender and media by examining the sentiments of YouTube commenters toward transgender characters. This investigation provides a unique insight into a contemporary audience’s perspective on gender equality. Employing natural language processing (NLP), public comments on YouTube related to broader discussions on gender and media were examined. Over 20,000 publicly typed comments and interactions concerning transgender characters in the Thai drama series Bai Mai Thi Plit Pliw (Falling Leaves) were analysed. The findings reveal that the majority of comments conveyed neutral sentiments, followed by negative and then positive sentiments. The audience experienced the highs and lows of the lives of the lead transwoman protagonist and the supporting transgender cast, negotiating emotions such as sympathy, depression, resentment, and happiness and expressing them in the comments. Furthermore, the audience demonstrated acceptance of transgender characters, including behaviours often deemed immoral, and for sentiments of self-love and vitality, while displays of domestic violence and class segregation received diminishing tolerance.
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