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Using Twitter for Nursing Research: A Tweet Analysis on Heat Illness and Health
Daniel J Smith1, Valerie V T Mac2, Vicki S Hertzberg3
1Alpha Epsilon, PhD Candidate and Clinical Instructor, Center for Data Science, Nell Hodgson Woodruff School of Nursing, Emory University, Atlanta, GA, USA.
Aim:
To provide an example of a tweet analysis for nurse researchers using Twitter in their research.
Design:
A content analysis using tweets about "heat illness + health."
Methods:
Tweets were pulled from Twitter's application programming interface with premium access using Postman and the key words "heat illness + health." All data cleaning and analysis was performed in R Version 3.5.2, and the tweet set was analyzed for term frequency, sentiment, and topic modeling. Principal R packages included LDAvis, tidytext, tm, and zyuzhet.
Results:
6,317 tweets were analyzed with a date range of April 6, 2009, to December 30, 2019. The most common terms in the tweets were heat (n = 4,532), illness (n = 4,085), and health (n = 2,257). Sentiment analysis showed that the majority of tweets (55%) had a negative sentiment. Topic modeling showed that there were three topics within the tweet set: increasing impact, prevention and safety, and symptoms.
Conclusions:
Twitter can be a useful tool for nursing researchers, serving as a viable adjunct to current research methodologies. This practical example has facilitated a deeper understanding of the social media representation of heat illness and health that can be applied to other research.
Clinical Relevance:
Twitter serves as a tool for collecting health information for multiple groups, ranging from clinicians and researchers to patients. By utilizing the plethora of data that comes from the platform, we can work towards developing theories and interventions related to numerous health conditions and phenomena.
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