Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: May 27, 2024
Date Accepted: Dec 30, 2024
Warning: This is an author submission that is not peer-reviewed or edited.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.
Perception of Online Communities towards the Use of Cancer Immunotherapy: A Data Mining Study of 3.6 Million Web-based Posts from Social Media Platforms Using BERTopic
ABSTRACT
Immunotherapy has become a game changer in cancer treatment. Few studies have investigated the perceptions about its use by analyzing social media data. This study aimed to use a topic modeling technique, BERTopic, to explore the perceptions of the online cancer communities regarding immunotherapy. A total of 4.9 million posts were extracted and preprocessed. BERTopic modeling was performed to identify topics from the posts, which were then broadly grouped into distinct themes. 3.6 million posts were remained for modeling after data cleaning. The highest overall topic quality achieved by BERTopic was 70.47% (topic diversity: 87.76%; topic coherence: 80.21%). BERTopic generated 14 topics related to the perceptions of immunotherapy, which were categorized into six themes. The themes primarily covered (1) hopeful prospects offered by immunotherapy, (2) perceived effectiveness of immunotherapy, (3) complementary therapies or self-treatments, (4) financial and mental impact of undergoing immunotherapy, (5) impact on lifestyle and time schedules, and (6) side effects due to treatment. This study provided an overview of the multifaceted considerations essential for the application of immunotherapy as a therapeutic intervention. Furthermore, it demonstrated the effectiveness of BERTopic in analyzing large amounts of data to identify perceptions underlying social media and online communities.
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