Monitoring real-time junior doctor sentiment from comments on a public social media platform: a retrospective observational study

情绪分析 观察研究 社会化媒体 医学 2019年冠状病毒病(COVID-19) 大流行 家庭医学 儿科 人工智能 病理 万维网 计算机科学 疾病 传染病(医学专业)
作者
Tamir Sirkis,Stuart Maitland
出处
期刊:Postgraduate Medical Journal [Oxford University Press]
卷期号:99 (1171): 423-427
标识
DOI:10.1136/pmj-2022-142080
摘要

Abstract Objectives To investigate whether sentiment analysis and topic modelling can be used to monitor the sentiment and opinions of junior doctors. Design Retrospective observational study based on comments on a social media website. Setting Every publicly available comment in r/JuniorDoctorsUK on Reddit from 1 January 2018 to 31 December 2021. Participants 7707 Reddit users who commented in the r/JuniorDoctorsUK subreddit. Main outcome measure Sentiment (scored −1 to +1) of comments compared with results of surveys conducted by the General Medical Council. Results Average comment sentiment was positive but varied significantly during the study period. Fourteen topics of discussion were identified, each associated with a different pattern of sentiment. The topic with the highest proportion of negative comments was the role of a doctor (38%), and the topic with the most positive sentiment was hospital reviews (72%). Conclusion Some topics discussed in social media are comparable to those queried in traditional questionnaires, whereas other topics are distinctive and offer insight into what themes junior doctors care about. Events during the coronavirus pandemic may explain the sentiment trends in the junior doctor community. Natural language processing shows significant potential in generating insights into junior doctors’ opinions and sentiment.

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