Public perception and changing attitudes toward antidepressants over a decade in social media: Lessons learned from online discussion using artificial intelligence

M Min Ho An M Min-Gyu Kim J Jueon Kim S Seheon Chang D Dong Yun Lee R Rae Woong Park

Abstract

Background Antidepressants play a crucial role in treating mental health disorders such as depression and anxiety. Understanding of patients’ perspective on antidepressants is essential for improving treatment outcomes; however, year-to-year change in the public’s perception of antidepressants remains unclear. We aimed to analyze changes in public sentiments and predominant perceptions regarding antidepressants using artificial intelligence pipeline. Methods This study analyzed online discussions related to antidepressants on Reddit from January 1, 2009, to December 31, 2022. Antidepressant-associated communities were explored to collect a list of discussions relevant to antidepressant therapy. Discussion topics on antidepressants were identified using BERTopic, and the sentiments were analyzed using a RoBERTa model. Trends were assessed using the Mann–Kendall test to evaluate shifts in sentiments over time. Results We analyzed 429,510 antidepressant-related discourse over 14 years and found a predominance in negative sentiments. Key discussion topics include the benefits and side effects of antidepressants, experiences with drug switching, and specific concerns regarding bupropion therapy. In trend analyses, negative sentiments decreased, while neutral sentiments increased over time. This aligns with a decline in the annual proportion of topics associated with side effects within each cluster. Conclusions Negative perceptions toward antidepressants are prevalent on social media, mainly focusing on efficacy and side effects. However, a decade-long analysis shows a decline in negative sentiments, with an increase in neutral sentiments with a downturn in yearly proportion of side-effected related topics within each cluster. These trends and information may help improve strategies to address barriers to antidepressant use and adherence.

Article Details

Journal PLoS ONE
Volume / Issue Vol. 20, Issue 9
Published September 04, 2025
Pages e0318464
ISSN 1932-6203
Publisher Public Library of Science

Journal Info

PLoS ONE

Public Library of Science

ISSN: 1932-6203 Open Access Health Sciences

Authors (6)

M

Min Ho An

M

Min-Gyu Kim

J

Jueon Kim

S

Seheon Chang

D

Dong Yun Lee

R

Rae Woong Park