ArticleEntropy (Basel, Switzerland)2022
Comparative Analysis of Social Support in Online Health Communities Using a Word Co-Occurrence Network Analysis Approach.
Article in Entropy (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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.
The trial behind it
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Who cites it
4 citing papers in PubMed.
- Analysis of the Behavioral Performance and Social Support of Patients in Online Health Communities From User Profile Perspectives: Comparative Study.Journal of medical Internet research · 2025Article
- NETWORK-BASED MODELING OF EMOTIONAL EXPRESSIONS FOR MULTIPLE CANCERS VIA A LINGUISTIC ANALYSIS OF AN ONLINE HEALTH COMMUNITY.The annals of applied statistics · 2025Article
- Natural language processing reveals network structure of pain communication in social media using discrete mathematical analysis.Scientific reports · 2025Article
- Deciphering the Diversity of Mental Models in Neurodevelopmental Disorders: Knowledge Graph Representation of Public Data Using Natural Language Processing.Journal of medical Internet research · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Online health communities (OHCs) have become a major source of social support for people with health problems. Members of OHCs interact online with others facing similar health problems and receive multiple types of social support, including but not limited to informational support, emotional support, and companionship. The aim of this study is to examine the differences in social support communication among people with different types of cancers. A novel approach is developed to better understand the types of social support embedded in OHC posts. Our approach, based on the word co-occurrence network analysis, preserves the semantic structures of the texts. Information extraction from the semantic structures is supported by the interplay of quantitative and qualitative analyses of the network structures. Our analysis shows that significant differences in social support exist across cancer types, and evidence for the differences across diseases in terms of communication preferences and language use is also identified. Overall, this study can establish a new venue for extracting and analyzing information, so as to inform social support for clinical care.
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Registered trials
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