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Using Social Media to Identify Consumers’ Sentiments towards Attributes of Health Insurance during Enrollment Season

Center for Health Services Research, The Larner College of Medicine, University of Vermont, Burlington, VT 05405, USA
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Appl. Sci. 2019, 9(10), 2035; https://doi.org/10.3390/app9102035
Received: 27 April 2019 / Revised: 9 May 2019 / Accepted: 13 May 2019 / Published: 17 May 2019
(This article belongs to the Special Issue Sentiment Analysis for Social Media)
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Abstract

This study aims to identify sentiments that consumers have about health insurance by analyzing what they discuss on Twitter. The objective was to use sentiment analysis to identify attitudes consumers express towards health insurance and health care providers. We used an Application Programming Interface to gather tweets from Twitter with the words “health insurance” or “health plan” during health insurance enrollment season in the United States in 2016‒2017. Word association was used to find words associated with “premium,” “access,” “network,” and “switch.” Sentiment analysis established which specific emotions were associated with insurance and medical providers, using the NRC Emotion Lexicon, identifying emotions. We identified that provider networks, prescription drug benefits, political preferences, and norms of other consumers matter. Consumers trust medical providers but they fear unexpected health events. The results suggest that there is a need for different algorithms to help consumers find the plans they want and need. Consumers buying health insurance in the Affordable Care Act marketplaces in the United States choose lower-cost plans with limited benefits, but at the same time express fear about unexpected health events and unanticipated costs. If we better understand the origin of the sentiments that drive consumers, we may be able to help them better navigate insurance plan options and insurers can better respond to their needs. View Full-Text
Keywords: social media; Twitter; text mining; sentiment analysis; word association; health insurance; provider networks social media; Twitter; text mining; sentiment analysis; word association; health insurance; provider networks
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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van den Broek-Altenburg, E.M.; Atherly, A.J. Using Social Media to Identify Consumers’ Sentiments towards Attributes of Health Insurance during Enrollment Season. Appl. Sci. 2019, 9, 2035.

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