Understanding topics and sentiment in an online cancer survivor community

Kenneth Portier, Greta E. Greer, Lior Rokach, Nir Ofek, Yafei Wang, Prakhar Biyani, Mo Yu, Siddhartha Banerjee, Kang Zhao, Prasenjit Mitra, John Yen

Research output: Contribution to journalArticlepeer-review

79 Scopus citations

Abstract

Online cancer communities help members support one another, provide new perspectives about living with cancer, normalize experiences, and reduce isolation. The American Cancer Society's 166000-member Cancer Survivors Network (CSN) is the largest online peer support community for cancer patients, survivors, and caregivers. Sentiment analysis and topic modeling were applied to CSN breast and colorectal cancer discussion posts from 2005 to 2010 to examine how sentiment change of thread initiators, a measure of social support, varies by discussion topic. The support provided in CSN is highest for medical, lifestyle, and treatment issues. Threads related to 1) treatments and side effects, surgery, mastectomy and reconstruction, and decision making for breast cancer, 2) lung scans, and 3) treatment drugs in colon cancer initiate with high negative sentiment and produce high average sentiment change. Using text mining tools to assess sentiment, sentiment change, and thread topics provides new insights that community managers can use to facilitate member interactions and enhance support outcomes.

Original languageEnglish (US)
Article numberlgt025
Pages (from-to)195-198
Number of pages4
JournalJournal of the National Cancer Institute - Monographs
Issue number47
DOIs
StatePublished - Dec 2013

All Science Journal Classification (ASJC) codes

  • Oncology
  • Cancer Research

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