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Currently accepted at: Journal of Medical Internet Research

Date Submitted: Mar 9, 2018
Open Peer Review Period: Mar 9, 2018 - Aug 7, 2018
Date Accepted: Aug 7, 2018
(closed for review but you can still tweet)

This paper has been accepted and is currently in production.

It will appear shortly on 10.2196/10043

The final accepted version (not copyedited yet) is in this tab.

The final, peer-reviewed published version of this preprint can be found here:

Using Twitter to Examine Web-Based Patient Experience Sentiments in the United States: Longitudinal Study

Sewalk KC, Tuli G, Hswen Y, Brownstein JS, Hawkins JB

Using Twitter to Examine Web-Based Patient Experience Sentiments in the United States: Longitudinal Study

J Med Internet Res 2018;20(10):e10043

DOI: 10.2196/10043

PMID: 30314959

PMCID: 6231860

Using Twitter to Examine Web-Based Patient Experience Sentiments in the United States: Longitudinal Study

  • Kara C Sewalk; 
  • Gaurav Tuli; 
  • Yulin Hswen; 
  • John S Brownstein; 
  • Jared B Hawkins

ABSTRACT

Background:

There are documented differences in access to health care across the United States. Previous research indicates that Web-based data regarding patient experiences and opinions of health care are available from Twitter. Sentiment analyses of Twitter data can be used to examine differences in patient views of health care across the United States.

Objective:

The objective of our study was to provide a characterization of patient experience sentiments across the United States on Twitter over a 4-year period.

Methods:

Using data from Twitter, we developed a set of 4 software components to automatically label and examine a database of tweets discussing patient experience. The set includes a classifier to determine patient experience tweets, a geolocation inference engine for social data, a modified sentiment classifier, and an engine to determine if the tweet is from a metropolitan or nonmetropolitan area in the United States. Using the information retrieved, we conducted spatial and temporal examinations of tweet sentiments at national and regional levels. We examined trends in the time of the day and that of the week when tweets were posted. Statistical analyses were conducted to determine if any differences existed between the discussions of patient experience in metropolitan and nonmetropolitan areas.

Results:

We collected 27.3 million tweets between February 1, 2013 and February 28, 2017, using a set of patient experience-related keywords; the classifier was able to identify 2,759,257 tweets labeled as patient experience. We identified the approximate location of 31.76% (876,384/2,759,257) patient experience tweets using a geolocation classifier to conduct spatial analyses. At the national level, we observed 27.83% (243,903/876,384) positive patient experience tweets, 36.22% (317,445/876,384) neutral patient experience tweets, and 35.95% (315,036/876,384) negative patient experience tweets. There were slight differences in tweet sentiments across all regions of the United States during the 4-year study period. We found the average sentiment polarity shifted toward less negative over the study period across all the regions of the United States. We observed the sentiment of tweets to have a lower negative fraction during daytime hours, whereas the sentiment of tweets posted between 8 pm and 10 am had a higher negative fraction. Nationally, sentiment scores for tweets in metropolitan areas were found to be more extremely negative and mildly positive compared with tweets in nonmetropolitan areas. This result is statistically significant (P<.001). Tweets with extremely negative sentiments had a medium effect size (d=0.34) at the national level.

Conclusions:

This study presents methodologies for a deeper understanding of Web-based discussion related to patient experience across space and time and demonstrates how Twitter can provide a unique and unsolicited perspective from users on the health care they receive in the United States.


 Citation

Please cite as:

Sewalk KC, Tuli G, Hswen Y, Brownstein JS, Hawkins JB

Using Twitter to Examine Web-Based Patient Experience Sentiments in the United States: Longitudinal Study

Journal of Medical Internet Research. (forthcoming/in press)

DOI: 10.2196/10043

URL: https://preprints.jmir.org/preprint/10043

PMID: 30314959

PMCID: 6231860

© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.