TY - JOUR
T1 - Understanding topics and sentiment in an online cancer survivor community
AU - Portier, Kenneth
AU - Greer, Greta E.
AU - Rokach, Lior
AU - Ofek, Nir
AU - Wang, Yafei
AU - Biyani, Prakhar
AU - Yu, Mo
AU - Banerjee, Siddhartha
AU - Zhao, Kang
AU - Mitra, Prasenjit
AU - Yen, John
PY - 2013/12
Y1 - 2013/12
N2 - 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.
AB - 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.
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U2 - 10.1093/jncimonographs/lgt025
DO - 10.1093/jncimonographs/lgt025
M3 - Article
C2 - 24395991
AN - SCOPUS:84892456267
SN - 1052-6773
SP - 195
EP - 198
JO - Journal of the National Cancer Institute - Monographs
JF - Journal of the National Cancer Institute - Monographs
IS - 47
M1 - lgt025
ER -