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 cancer 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 Twitter’s public streaming API, we
compiled over 5.3 million “breast 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 cancer patient experiences. We analyzed a sample of 845 breast cancer
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