ArticleJMIR public health and surveillance2020
Classification of Health-Related Social Media Posts: Evaluation of Post Content-Classifier Models and Analysis of User Demographics.
Article in JMIR public health and surveillance, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed.
- HPV vaccine misinformation on social media: A multi-method qualitative analysis of comments across three platforms.PEC innovation · 2024Article
- Motivational Influences Affecting Middle-Aged and Elderly Users' Participation Intention in Health-Related Social Media.International journal of environmental research and public health · 2022Article
- Human Papillomavirus Vaccine Messaging on TikTok: Social Media Content Analysis.Health promotion practice · 2022Article
- An Exploration of e-Cigarette-Related Search Items on YouTube: Network Analysis.Journal of medical Internet research · 2022Article
- Recommendations From the Twitter Hashtag #DoctorsAreDickheads: Qualitative Analysis.Journal of medical Internet research · 2020Article
- YouTube Video Comments on Healthy Eating: Descriptive and Predictive Analysis.JMIR public health and surveillance · 2020Article
- Using Twitter to Surveil the Opioid Epidemic in North Carolina: An Exploratory Study.JMIR public health and surveillance · 2020Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe increasing volume of health-related social media activity, where users connect, collaborate, and engage, has increased the significance of analyzing how people use health-related social media.
objectiveThe aim of this study was to classify the content (eg, posts that share experiences and seek support) of users who write health-related social media posts and study the effect of user demographics on post content.
methodsWe analyzed two different types of health-related social media: (1) health-related online forums-WebMD and DailyStrength-and (2) general online social networks-Twitter and Google+. We identified several categories of post content and built classifiers to automatically detect these categories. These classifiers were used to study the distribution of categories for various demographic groups.
resultsWe achieved an accuracy of at least 84% and a balanced accuracy of at least 0.81 for half of the post content categories in our experiments. In addition, 70.04% (4741/6769) of posts by male WebMD users asked for advice, and male users' WebMD posts were more likely to ask for medical advice than female users' posts. The majority of posts on DailyStrength shared experiences, regardless of the gender, age group, or location of their authors. Furthermore, health-related posts on Twitter and Google+ were used to share experiences less frequently than posts on WebMD and DailyStrength.
conclusionsWe studied and analyzed the content of health-related social media posts. Our results can guide health advocates and researchers to better target patient populations based on the application type. Given a research question or an outreach goal, our results can be used to choose the best online forums to answer the question or disseminate a message.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.