Direct-to-Consumer Genetic Testing on Social Media: Topic Modeling and Sentiment Analysis of YouTube Users' Comments

Abstract

Background With direct-to-consumer (DTC) genetic testing enabling self-responsible access to novel information on ancestry, traits, or health, consumers often turn to social media for assistance and discussion. YouTube, the largest social media platform for videos, offers an abundance of DTC genetic testing–related videos. Nevertheless, user discourse in the comments sections of these videos is largely unexplored. Objective This study aims to address the lack of knowledge concerning user discourse in the comments sections of DTC genetic testing–related videos on YouTube by exploring topics discussed and users' attitudes toward these videos. Methods We employed a 3-step research approach. First, we collected metadata and comments of the 248 most viewed DTC genetic testing–related videos on YouTube. Second, we conducted topic modeling using word frequency analysis, bigram analysis, and structural topic modeling to identify topics discussed in the comments sections of those videos. Finally, we employed Bing (binary), National Research Council Canada (NRC) emotion, and 9-level sentiment analysis to identify users' attitudes toward these DTC genetic testing–related videos, as expressed in their comments. Results We collected 84,082 comments from the 248 most viewed DTC genetic testing–related YouTube videos. With topic modeling, we identified 6 prevailing topics on (1) general genetic testing, (2) ancestry testing, (3) relationship testing, (4) health and trait testing, (5) ethical concerns, and (6) YouTube video reaction. Further, our sentiment analysis indicates strong positive emotions (anticipation, joy, surprise, and trust) and a neutral-to-positive attitude toward DTC genetic testing–related videos. Conclusions With this study, we demonstrate how to identify users' attitudes on DTC genetic testing by examining topics and opinions based on YouTube video comments. Shedding light on user discourse on social media, our findings suggest that users are highly interested in DTC genetic testing and related social media content. Nonetheless, with this novel market constantly evolving, service providers, content providers, or regulatory authorities may still need to adapt their services to users' interests and desires.

Rol de autoridad y análisis del discurso en torno al cáncer de mama en las comunidades de YouTube

“…Asimismo, se ha empleado la herramienta de análisis de texto Topic Modeling (Vayansky;Kumar, 2020), que se ha trabajado con el algoritmo LDA (Sievert;Shirley, 2014), mediante el software Orange Data Mining para encontrar los patrones y temas dominantes en los videos (Miranda;Martin, 2020;Paul;Dredze, 2014). Además, se han estudiado los temas discutidos por los usuarios en las secciones de comentarios de esos videos (Toussaint et al, 2022) pensando que dicha información podría ser útil para comprender las preocupaciones y perspectivas de las personas interesadas en el tema. Para ello, en cada comunidad se han recopilado hasta 100 comentarios en cada uno de los 50 primeros e330303 Profesional de la información, 2024, v. 33, n. 3. e-ISSN: 1699-2407 5 videos con mayor grado de autoridad y se han ordenado para su estudio por número de likes.…”