Get Online Support, Feel Better-Sentiment Analysis and Dynamics in an Online Cancer Survivor Community.


Many users join online health communities (OHC) to obtain information and seek social support. Understanding the emotional impacts of participation on patients and their informal caregivers is important. Ethnographical observations, interviews, and questionnaires have reported benefits from online health communities, but these approaches are too costly to adopt for large-scale analyses of emotional impacts.

Research Questions:

How to analyze the benefits of emotional impacts of online interactions for cancer survivors in large scale? What attributes of online interactions affect these impacts?


A computational sentiment analysis approach using machine learning and text mining techniques is used to analyze 10-year data from the American Cancer Society Cancer Survivors Network (CSN).

Main Results:

This first study of sentiment benefits and dynamics in a large-scale health-related electronic community finds that an estimated 75%-85% of CSN forum participants change their sentiment in a positive direction through online interactions with other community members. Two new features, Name and Slang, not previously used in sentiment analysis, facilitate identifying positive sentiment in posts. Our study revealed, for the first time, that the number of participants and their average sentiments can affect the sentiment changes of thread initiators. More specifically, increasing the number of participants on a threadincreases the likelihood that the thread initiator has a positive sentimentchange. Furthermore, the more positive the average sentiment of participants on a thread is the more positive is the sentiment change of the thread initiators.

This work establishes foundational concepts for further studies of sentiment impact of OHC participation and provides insight useful for the design of new OHC's or enhancement of existing OHCs in providing better emotional support to their members.