title: Collecting and Analyzing Patient Experiences of Health Care From Social Media.
abstract: BACKGROUND
  Social Media, such as Yelp, provides rich information of consumer experience. Previous studies suggest that Yelp can serve as a new source to study patient experience. However, the lack of a corpus of patient reviews causes a major bottleneck for applying computational techniques.
  
  
  OBJECTIVE
  The objective of this study is to create a corpus of patient experience (COPE) and report descriptive statistics to characterize COPE.
  
  
  METHODS
  Yelp reviews about health care-related businesses were extracted from the Yelp Academic Dataset. Natural language processing (NLP) tools were used to split reviews into sentences, extract noun phrases and adjectives from each sentence, and generate parse trees and dependency trees for each sentence. Sentiment analysis techniques and Hadoop were used to calculate a sentiment score of each sentence and for parallel processing, respectively.
  
  
  RESULTS
  COPE contains 79,173 sentences from 6914 patient reviews of 985 health care facilities near 30 universities in the United States. We found that patients wrote longer reviews when they rated the facility poorly (1 or 2 stars). We demonstrated that the computed sentiment scores correlated well with consumer-generated ratings. A consumer vocabulary to describe their health care experience was constructed by a statistical analysis of word counts and co-occurrences in COPE.
  
  
  CONCLUSIONS
  A corpus called COPE was built as an initial step to utilize social media to understand patient experiences at health care facilities. The corpus is available to download and COPE can be used in future studies to extract knowledge of patients' experiences from their perspectives. Such information can subsequently inform and provide opportunity to improve the quality of health care.
authors.affiliation: Marshfield Clinic Research Foundation, Biomedical Informatics Research Center, Marshfield, WI, United States.
authors.forename: Majid
authors.identifier: http://orcid.org/0000-0001-6962-3554
authors.initials: M
authors.lastname: Rastegar-Mojarad
authors.forename: Zhan
authors.identifier: http://orcid.org/0000-0002-0426-0382
authors.initials: Z
authors.lastname: Ye
authors.forename: Daniel
authors.identifier: http://orcid.org/0000-0002-2005-7819
authors.initials: D
authors.lastname: Wall
authors.forename: Narayana
authors.identifier: http://orcid.org/0000-0002-0099-5330
authors.initials: N
authors.lastname: Murali
authors.forename: Simon
authors.identifier: http://orcid.org/0000-0003-2876-2042
authors.initials: S
authors.lastname: Lin
keywords: consumer health information; health care; natural language processing; patient satisfaction; social media