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Background Given the rapid development of social media, effective extraction and analysis of the contents of social media for health care have attracted widespread attention from health care providers. As far as we know, most of the reviews focus on the application of social media, and there is a lack of reviews that integrate the methods for analyzing social media information for health care. Objective This scoping review aims to answer the following 4 questions: (1) What types of research have been used to investigate social media for health care, (2) what methods have been used to analyze the existing health information on social media, (3) what indicators should be applied to collect and evaluate the characteristics of methods for analyzing the contents of social media for health care, and (4) what are the current problems and development directions of methods used to analyze the contents of social media for health care? Methods A scoping review following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines was conducted. We searched PubMed, the Web of Science, EMBASE, the Cumulative Index to Nursing and Allied Health Literature, and the Cochrane Library for the period from 2010 to May 2023 for primary studies focusing on social media and health care. Two independent reviewers screened eligible studies against inclusion criteria. A narrative synthesis of the included studies was conducted. Results Of 16,161 identified citations, 134 (0.8%) studies were included in this review. These included 67 (50.0%) qualitative designs, 43 (32.1%) quantitative designs, and 24 (17.9%) mixed methods designs. The applied research methods were classified based on the following aspects: (1) manual analysis methods (content analysis methodology, grounded theory, ethnography, classification analysis, thematic analysis, and scoring tables) and computer-aided analysis methods (latent Dirichlet allocation, support vector machine, probabilistic clustering, image analysis, topic modeling, sentiment analysis, and other natural language processing technologies), (2) categories of research contents, and (3) health care areas (health practice, health services, and health education). Conclusions Based on an extensive literature review, we investigated the methods for analyzing the contents of social media for health care to determine the main applications, differences, trends, and existing problems. We also discussed the implications for the future. Traditional content analysis is still the mainstream method for analyzing social media content, and future research may be combined with big data research. With the progress of computers, mobile phones, smartwatches, and other smart devices, social media information sources will become more diversified. Future research can combine new sources, such as pictures, videos, and physiological signals, with online social networking to adapt to the development trend of the internet. More medical information talents need to be trained in the future to better solve the problem of network information analysis. Overall, this scoping review can be useful for a large audience that includes researchers entering the field.

BACKGROUND Given the rapid development of social media, how to effectively extract and analysis contents of social media for health care has attracted widespread attention from healthcare providers. As far as we know, most of the reviews focus on the application of social media, and there is no review that integrates the methods for analyzing social information for health care. OBJECTIVE This scoping review aims to solve the two questions on (1) What types of research have been used to investigate social media for health care? (2) What methods have been used to analyze the existing health information on social media? METHODS A scoping review following PRISMA guidance was conducted. We searched PubMed, Web of Science, EMBASE, CINAHL, and Cochrane Library from inception to February 2022 for primary studies focused on social media and health care. Two independent reviewers screened eligible studies against inclusion criteria. A narrative synthesis of the included studies was conducted. RESULTS Of 10073 identified citations, 113 studies were included in the review. These included 58 qualitative designs, 33 quantitative designs, and 22 mixed-methods designs. The applied research methods are divided into manual analysis methods (content analysis methodology, grounded theory, ethnography, classification analysis, thematic analysis, and scoring table) and computer-aided analysis methods (latent Dirichlet allocation, support vector machine, probabilistic clustering, image analysis technology, natural language processing, topic modeling, and sentiment analysis). CONCLUSIONS Traditional content analysis is still the mainstream of social media information analysis, and future research may be combined with big data research. With the progress of computers, mobile phones, smart watches, and other smart devices, social media information sources will become more diversified. Future research can combine new sources such as pictures, videos, and physiological signals with online social networking to adapt to the development trend of the internet. More medical information talents need to be trained in the future to better solve the problem of network information analysis.

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