DisVis: Visualizing Discussion Threads in Online Health Communities
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Updated: Mar 6, 2026

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community
Published on: May 31, 2019
Drashko Nakikj1, Lena Mamykina1
1Department of Biomedical Informatics, Columbia University, New York, NY, USA.
Abstract:
An increasing number of individuals turn to online health communities (OHC) for information, advice and support about their health condition or disease. As a result of users' active participation, these forums store overwhelming volumes of information, which can make access to this information challenging and frustrating. To help overcome this problem we designed a discussion visualization tool DisVis. DisVis includes features for overviewing, browsing and finding particular information in a discussion. In a between subjects study, we tested the impact of DisVis on individuals' ability to provide an overview of a discussion, find topics of interest and summarize opinions. The study showed that after using the tool, the accuracy of participants' answers increased by 68% (p-value = 0.023) while at the same time exhibiting trends for reducing the time to answer by 38% with no statistical significance (p-value = 0.082). Qualitative interviews showed general enthusiasm regarding tools for improving browsing and searching for information within discussion forums, suggested different usage scenarios, highlighted opportunities for improving the design of DisVis, and outlined new directions for visualizing user-generated content within OHCs.
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