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Accepted for/Published in: JMIR Infodemiology

Date Submitted: Apr 14, 2022
Date Accepted: Aug 18, 2022

The final, peer-reviewed published version of this preprint can be found here:

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

Toussaint PA, Renner M, Lins S, Thiebes S, Sunyaev A

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

JMIR Infodemiology 2022;2(2):e38749

DOI: 10.2196/38749

PMID: 37113449

PMCID: 10014090

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Direct-to-Consumer Genetic Testing in Social Media: Analysis of YouTube Users' Comments

  • Philipp A Toussaint; 
  • Maximilian Renner; 
  • Sebastian Lins; 
  • Scott Thiebes; 
  • Ali Sunyaev

ABSTRACT

Background:

With direct-to-consumer (DTC) genetic testing allowing consumers self-responsible access to novel information on their ancestry, traits, or health, consumers often turn to social media for assistance and discussion. While YouTube, the largest social media platform for videos, offers an abundance of DTC genetic testing-related videos, 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 utilizing word frequency analysis, bi-gram analysis, and structural topic modeling to identify topics discussed in the comment sections of those videos. Last, we employed Bing (binary), NRC emotion, and 9-level sentiment analysis to identify users’ attitudes toward these DTC genetic testing-related videos, as expressed in the comments.

Results:

We collected 84,082 comments from the 248 most viewed DTC genetic testing-related YouTube videos. With the topic modeling, we identified six 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 in 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.


 Citation

Please cite as:

Toussaint PA, Renner M, Lins S, Thiebes S, Sunyaev A

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

JMIR Infodemiology 2022;2(2):e38749

DOI: 10.2196/38749

PMID: 37113449

PMCID: 10014090

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