Loading...

Media is loading
 

Paper Type

ERF

Description

Online cancer communities (OCCs) are crucial resources for cancer patients, providing support for the complex and challenging aspects of the disease. Patients often face unique problems, and OCCs offer a place to seek support when friends and family may not understand. This study explores how unique topics discussed in OCCs impact user participation in a thread, measured by the number of replies, repliers, length of replies, and response speed. A deep-learning-based natural language processing topic model is used to calculate the uniqueness scores of posts in OCCs, based on the prevalence of each topic. The study has implications for OCC administrators, researchers, and physicians in terms of understanding and addressing unique health topics expressed in online communities.

Paper Number

1750

Comments

SIG Health

Download

Share

COinS
 
Aug 10th, 12:00 AM

How the Uniqueness of Initial Posts Affect User Participation in Online Cancer Communities

Online cancer communities (OCCs) are crucial resources for cancer patients, providing support for the complex and challenging aspects of the disease. Patients often face unique problems, and OCCs offer a place to seek support when friends and family may not understand. This study explores how unique topics discussed in OCCs impact user participation in a thread, measured by the number of replies, repliers, length of replies, and response speed. A deep-learning-based natural language processing topic model is used to calculate the uniqueness scores of posts in OCCs, based on the prevalence of each topic. The study has implications for OCC administrators, researchers, and physicians in terms of understanding and addressing unique health topics expressed in online communities.

When commenting on articles, please be friendly, welcoming, respectful and abide by the AIS eLibrary Discussion Thread Code of Conduct posted here.