Twitter Sentiment Predicts Affordable Care Act Marketplace Enrollment

Wong, Charlene A.; Sap, Maarten; Schwartz, Andrew D.; Town, Robert J.; Baker, Thomas L.; Ungar, Lyle H.; Merchant, Raina M.

doi:10.2196/jmir.3812

Cited by 46 publications

(26 citation statements)

References 23 publications

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“… 33 34 Researchers have also been experimenting with sentiment analysis of social media for healthcare research. 13 14 16 17 Sentiment can be determined in several ways, with the goal being to classify the underlying emotional information as either positive or negative. This can be done either purely by human input or by an algorithm trained to complete this process based on a human-classified set of objects, and reliability is largely a function of the method used.…”

Section: Introductionmentioning

confidence: 99%

Measuring patient-perceived quality of care in US hospitals using Twitter

Hawkins¹,

et al. 2015

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BackgroundPatients routinely use Twitter to share feedback about their experience receiving healthcare. Identifying and analysing the content of posts sent to hospitals may provide a novel real-time measure of quality, supplementing traditional, survey-based approaches.ObjectiveTo assess the use of Twitter as a supplemental data stream for measuring patient-perceived quality of care in US hospitals and compare patient sentiments about hospitals with established quality measures.Design404 065 tweets directed to 2349 US hospitals over a 1-year period were classified as having to do with patient experience using a machine learning approach. Sentiment was calculated for these tweets using natural language processing. 11 602 tweets were manually categorised into patient experience topics. Finally, hospitals with ≥50 patient experience tweets were surveyed to understand how they use Twitter to interact with patients.Key resultsRoughly half of the hospitals in the US have a presence on Twitter. Of the tweets directed toward these hospitals, 34 725 (9.4%) were related to patient experience and covered diverse topics. Analyses limited to hospitals with ≥50 patient experience tweets revealed that they were more active on Twitter, more likely to be below the national median of Medicare patients (p<0.001) and above the national median for nurse/patient ratio (p=0.006), and to be a nonprofit hospital (p<0.001). After adjusting for hospital characteristics, we found that Twitter sentiment was not associated with Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) ratings (but having a Twitter account was), although there was a weak association with 30-day hospital readmission rates (p=0.003).ConclusionsTweets describing patient experiences in hospitals cover a wide range of patient care aspects and can be identified using automated approaches. These tweets represent a potentially untapped indicator of quality and may be valuable to patients, researchers, policy makers and hospital administrators.

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Section: Introductionmentioning

confidence: 99%

Measuring patient-perceived quality of care in US hospitals using Twitter

Hawkins¹,

et al. 2015

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“…Computerized content analysis utilizing techniques such as natural language processing (NPL) show great promise (Wong et al, 2015). However, these techniques focus on social media language in isolation of conversation.…”

Section: Analysis and Interpretationmentioning

confidence: 99%

Social Media in the Sexual Lives of African American and Latino Youth: Challenges and Opportunities in the Digital Neighborhood

Stevens

Dunaev

Malven

et al. 2016

MaC

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There has been significant interest in the role of social media in the lives of adolescents, particularly as it relates to sexual risk. Researchers have focused on understanding usage behaviors, quantifying effects of social media exposure and activity, and using social media to intervene. Much of this work has focused on college students and non-minority youth. In this paper, we examine the growing body of literature around social media use among US minority youth and its intersection with sexual risk behavior. We introduce the concept of the "digital neighborhood" and examine the intersection of social media and sexual health in two domains: 1) sexual content in social media and 2) evidence of social media effects on sexual behavior. Finally, we discuss the opportunities and challenges for researchers and practitioners engaging youth of color.

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“…One study of postings on a weight-loss blog suggested that sharing one’s negative emotions, as indicated by the use of sadness words, was linked to greater success in losing weight [ 5 ]. Similar explorations of social media as a way to understand health attitudes and behavior (eg, [ 6 - 8 ]) and track health outcomes (eg, [ 9 , 10 ]) further illustrate the potential in exploring social media data to establish their utility for policy uses.…”

Section: Introductionmentioning

confidence: 96%

“…Research on Twitter data suggests that sentiment (as indicated by word use) in tweets can be used to model life satisfaction [ 7 ], happiness [ 6 ], and heart disease mortality [ 10 ] and health. Sentiment revealed in social media data can also help predict engagement in healthy behaviors, such as health insurance enrollment [ 8 ].…”

Section: Introductionmentioning

confidence: 99%

Social Media as a Catalyst for Policy Action and Social Change for Health and Well-Being: Viewpoint

Yeung¹

2018

J Med Internet Res

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This viewpoint paper argues that policy interventions can benefit from the continued use of social media analytics, which can serve as an important complement to traditional social science data collection and analysis. Efforts to improve well-being should provide an opportunity to explore these areas more deeply, and encourage the efforts of those conducting national and local data collection on health to incorporate more of these emerging data sources.Social media remains a relatively untapped source of information to catalyze policy action and social change. However, the diversity of social media platforms and available analysis techniques provides multiple ways to offer insight for policy making and decision making. For instance, social media content can provide timely information about the impact of policy interventions. Social media location information can inform where to deploy resources or disseminate public messaging. Network analysis of social media connections can reveal underserved populations who may be disconnected from public services. Machine learning can help recognize important patterns for disease surveillance or to model population sentiment. To fully realize these potential policy uses, limitations to social media data will need to be overcome, including data reliability and validity, and potential privacy risks.Traditional data collection may not fully capture the upstream factors and systemic relationships that influence health and well-being. Policy actions and social change efforts, such as the Robert Wood Johnson Foundation’s effort to advance a culture of health, which are intended to drive change in a network of upstream health drivers, will need to incorporate a broad range of behavioral information, such as health attitudes or physical activity levels. Applying innovative techniques to emerging data has the potential to extract insight from unstructured data or fuse disparate sources of data, such as linking health attitudes that are expressed to health behaviors or broader health and well-being outcomes.

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Twitter Sentiment Predicts Affordable Care Act Marketplace Enrollment

Cited by 46 publications

References 23 publications

Measuring patient-perceived quality of care in US hospitals using Twitter

Measuring patient-perceived quality of care in US hospitals using Twitter

Social Media in the Sexual Lives of African American and Latino Youth: Challenges and Opportunities in the Digital Neighborhood

Social Media as a Catalyst for Policy Action and Social Change for Health and Well-Being: Viewpoint

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