ArticleJMIR cancer2021
Understanding Communication in an Online Cancer Forum: Content Analysis Study.
Article in JMIR cancer, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 16 citations in OpenAlex.
- Exploring the Narratives of Patients With Cancer Using Large Language Models: Topic Modeling and Social Network Analysis.Journal of medical Internet research · 2026Article
- Bridging functional bionanomaterials and the clinic: strategic communication as a translational enabler.Journal of nanobiotechnology · 2026Review
- The Association Between Linguistic Characteristics of Physicians' Communication and Their Economic Returns: Mixed Method Study.Journal of medical Internet research · 2024Article
- Predicting negative attitudes towards suicide in social media texts: prediction model development and validation study.Frontiers in public health · 2024Article
- Use of Online Health Forums by People Living With Breast Cancer During the COVID-19 Pandemic: Thematic Analysis.JMIR cancer · 2023Article
- Article
- 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
- Article
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCancer affects individuals, their family members, and friends, and increasingly, some of these individuals are turning to online cancer forums to express their thoughts/feelings and seek support such as asking cancer-related questions. The thoughts/feelings expressed and the support needed from these online forums may differ depending on if (1) an individual has or had cancer or (2) an individual is a family member or friend of an individual who has or had cancer; the language used in posts in these forums may reflect these differences.
objectiveUsing natural language processing methods, we aim to determine the differences in the support needs and concerns expressed in posts published on an online cancer forum by (1) users who self-declare to have or had cancer compared with (2) users who self-declare to be family members or friends of individuals with or that had cancer.
methodsUsing latent Dirichlet allocation (LDA), which is a natural language processing algorithm and Linguistic Inquiry and Word Count (LIWC), a psycholinguistic dictionary, we analyzed posts published on an online cancer forum with the aim to delineate the language features associated with users in these different groups.
resultsUsers who self-declare to have or had cancer were more likely to post about LDA topics related to hospital visits (Cohen d=0.671) and use words associated with LIWC categories related to health (Cohen d=0.635) and anxiety (Cohen d=0.126). By contrast, users who declared to be family members or friends tend to post about LDA topics related to losing a family member (Cohen d=0.702) and LIWC categories focusing on the past (Cohen d=0.465) and death (Cohen d=0.181) were more associated with these users.
conclusionsUsing LDA and LIWC, we show that there are differences in the support needs and concerns expressed in posts published on an online cancer forum by users with cancer compared with family members or friends of those with cancer. Hence, responders to online cancer forums need to be cognizant of these differences in support needs and concerns and tailor their responses based on these findings.
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