Evidence map›Paper›PMID 41915425›Full record

ArticleJMIR infodemiology2026

Understanding Social Support and Opinion Leaders in a Tuberculosis-Related Online Community in China: Content and Network Analyses.

Xiaojun Fan, Jueman Zhang, Xiuli Wang

Abstract read
In one paragraph

Article in JMIR infodemiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Xiaojun FanSchool of New Media, Peking University, Beijing, China.ORCID 0009-0002-4539-9214
Jueman ZhangHarrington School of Communication and Media, University of Rhode Island, Kingston, RI, United States.ORCID 0000-0002-2653-5914
Xiuli WangSchool of New Media, Peking University, Beijing, China.ORCID 0000-0001-6954-7475

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTuberculosis (TB) remains one of the world's deadliest infectious diseases. Yet, despite the growing role of online health communities (OHCs) as key sources of social support, research on TB-related online communities remains scarce. Network analysis has been increasingly used to study OHCs and identify opinion leaders (OLs), offering a valuable approach to advancing knowledge about TB-related online communities.

objectiveThis study examined the types of social support and the influence of OLs in a prominent TB-related online forum in China, with a particular focus on its curated subforum that served as a centralized space for user interaction. The subforum consisted of posts recommended by the forum's administrator and the corresponding user replies they generated.

methodsThe data consisted of all 438 administrator-recommended posts and the 150,570 associated user replies over 18 years, from the forum's launch in 2004 to 2021. The study used content analysis to examine the types of social support present in administrator-recommended posts, which are commonly considered high-quality. It then applied social network analysis to these posts and their associated user replies to identify OLs by using a Borda ranking method based on centrality measures and user tenure. Finally, semantic network analysis was used to explore topic clusters within each OL's posts and their associated user replies.

resultsThe content analysis showed a high prevalence of informational and emotional support in the administrator-recommended posts. Of the 438 posts, 296 (67.5%) contained social support, with 150 containing informational support and 136 containing emotional support. Social support varied by post theme and whether the intent was to provide or seek it. Among disease knowledge posts, 74 out of 75 provided informational support. Emotional support was most frequently provided in nontreatment sharing posts (28/113) and most frequently sought in treatment experience posts (47/129). The social network analysis identified 10 OLs. The first was a former patient with TB, and the second was a pulmonary TB doctor. Together, they contributed 30.4% (133/438) of all the posts. Across the semantic network analyses of each OL's posts and their associated user replies, informational support was more prominent than emotional support.

conclusionsThe findings suggest that the examined TB-related online forum served as an important source of social support for people affected by TB in China, fostering an environment for both informational and emotional support. OLs played an important role by contributing posts and establishing a central position through reply interactions with users.

Indexed as

LeadershipSocial SupportTuberculosisChinaHumansInternetSocial Network AnalysisOHConline health communityopinion leadersemantic network analysissocial network analysissocial supportTBtuberculosis

Identifiers

PMID41915425
PMCPMC13080297

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