Title
A Sentiment Analysis of Breast Cancer Treatment Experiences and Healthcare Perceptions Across Twitter.
Abstract
Background: Social media has the capacity to afford the healthcare industry with valuable feedback from patients who reveal and express their medical decision-making process, as well as self-reported quality of life indicators both during and post treatment. In prior work, [Crannell et. al.], we have studied an active patient population on Twitter and compiled a set of tweets describing their experience with this disease. We refer to these online public testimonies as Invisible Patient Reported Outcomes (iPROs), because they carry relevant indicators, yet are difficult to capture by conventional means of self-report. Methods: Our present study aims to identify tweets related to the patient experience as an additional informative tool for monitoring public health. Using Twitteru0027s public streaming API, we compiled over 5.3 million cancer related tweets spanning September 2016 until mid December 2017. We combined supervised machine learning methods with natural language processing to sift tweets relevant to breast patient experiences. We analyzed a sample of 845 breast patient and survivor accounts, responsible for over 48,000 posts. We investigated tweet content with a hedonometric sentiment analysis to quantitatively extract emotionally charged topics. Results: We found that positive experiences were shared regarding patient treatment, raising support, and spreading awareness. Further discussions related to healthcare were prevalent and largely negative focusing on fear of political legislation that could result in loss of coverage. Conclusions: Social media can provide a positive outlet for patients to discuss their needs and concerns regarding their healthcare coverage and treatment needs. Capturing iPROs from online communication can help inform healthcare professionals and lead to more connected and personalized treatment regimens.
Year
Venue
Field
2018
arXiv: Computation and Language
Health care,Public health,Population,Internet privacy,Social media,Breast cancer,Computer science,Sentiment analysis,Legislation,Natural language processing,Artificial intelligence,Patient experience
DocType
Volume
Citations 
Journal
abs/1805.09959
0
PageRank 
References 
Authors
0.34
0
7
Name
Order
Citations
PageRank
Eric M. Clark1292.71
Ted James200.34
c a jones3271.68
Amulya Alapati400.34
Promise Ukandu500.34
Christopher M. Danforth657347.23
Peter Sheridan Dodds760350.13