Artificial Intelligence–Enabled Analysis of Statin-Related Topics and Sentiments on Social Media

Abstract

ImportanceDespite compelling evidence that statins are safe, are generally well tolerated, and reduce cardiovascular events, statins are underused even in patients with the highest risk. Social media may provide contemporary insights into public perceptions about statins.ObjectiveTo characterize and classify public perceptions about statins that were gleaned from more than a decade of statin-related discussions on Reddit, a widely used social media platform.Design, Setting, and ParticipantsThis qualitative study analyzed all statin-related discussions on the social media platform that were dated between January 1, 2009, and July 12, 2022. Statin- and cholesterol-focused communities, were identified to create a list of statin-related discussions. An artificial intelligence (AI) pipeline was developed to cluster these discussions into specific topics and overarching thematic groups. The pipeline consisted of a semisupervised natural language processing model (BERT [Bidirectional Encoder Representations from Transformers]), a dimensionality reduction technique, and a clustering algorithm. The sentiment for each discussion was labeled as positive, neutral, or negative using a pretrained BERT model.ExposuresStatin-related posts and comments containing the terms statin and cholesterol.Main Outcomes and MeasuresStatin-related topics and thematic groups.ResultsA total of 10 233 unique statin-related discussions (961 posts and 9272 comments) from 5188 unique authors were identified. The number of statin-related discussions increased by a mean (SD) of 32.9% (41.1%) per year. A total of 100 discussion topics were identified and were classified into 6 overarching thematic groups: (1) ketogenic diets, diabetes, supplements, and statins; (2) statin adverse effects; (3) statin hesitancy; (4) clinical trial appraisals; (5) pharmaceutical industry bias and statins; and (6) red yeast rice and statins. The sentiment analysis revealed that most discussions had a neutral (66.6%) or negative (30.8%) sentiment.Conclusions and RelevanceResults of this study demonstrated the potential of an AI approach to analyze large, contemporary, publicly available social media data and generate insights into public perceptions about statins. This information may help guide strategies for addressing barriers to statin use and adherence.

Contemporary attitudes and beliefs on coronary artery calcium from social media using artificial intelligence

“…Our AI-enabled analysis of public perceptions of CAC testing demonstrates how well our previously described algorithm for topic modeling generalizes to another clinical domain 8 . A powerful aspect of our pipeline is leveraging techniques in unsupervised machine learning that obviate the need for topic prespecification, which allows discovery of previously unexpected ideas (e.g., non-evidence-based use of CAC).…”

“…Details around topic modeling and sentiment analysis in this paper are described elsewhere 8 . Briefly, after preprocessing, discussions are embedded into a numerical representation using a pretrained, sentence-level Bidirectional Encoder Representations from Transformers (BERT) model called all-MiniLM-L6-v2 19 , which has been trained on over 600 million Reddit posts and a dataset containing over 12 million papers from medical journals.…”

“…Understanding these beliefs about CAC is critical, as it may help frame shared decision-making discussions and guide public health interventions around ASCVD. Artificial intelligence (AI)-enabled analysis of large volumes of social media data can provide an efficient approach for analyzing contemporary public opinions on common health-related topics and allow for a systematic evaluation of emerging themes 8 . Reddit is a free and widely used social media platform with over 52 million daily active users and over 30 billion views every month 9 .…”

Statin Twitter: Human and Automated Bot Contributions, 2010 to 2022

“…Misinformation is an important driver of nonuse and is prevalent in online forums, affecting patients and clinicians alike. 8 , 9 , 10 …”

“… 11 A recent analysis of Reddit data found that the average sentiment of statin‐related content was neutral to negative and that the most common themes were alternative lipid‐lowering methods, adverse effects, and statin hesitancy. 10 Compared with Reddit, Twitter is even more widely used. 12 Twitter is among the most influential social media platforms, with ≈145 million daily users and 330 million monthly users.…”