Understanding the Engagement and Interaction of Superusers and Regular Users in UK Respiratory Online Health Communities: Deep Learning-Based Sentiment Analysis.

ABSTRACT:

Background

Online health communities (OHCs) enable people with long-term conditions (LTCs) to exchange peer self-management experiential information, advice, and support. Engagement of "superusers," that is, highly active users, plays a key role in holding together the community and ensuring an effective exchange of support and information. Further studies are needed to explore regular users' interactions with superusers, their sentiments during interactions, and their ultimate impact on the self-management of LTCs.

Objective

This study aims to gain a better understanding of sentiment distribution and the dynamic of sentiment of posts from 2 respiratory OHCs, focusing on regular users' interaction with superusers.

Methods

We conducted sentiment analysis on anonymized

SUBMITTER: Li X 

PROVIDER: S-EPMC11888069 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature