Abstract
Natural language processing techniques have increased the volume and variety of text data that can be analyzed. The aim of this study was to identify the positive and negative topical sentiments among diet, diabetes, exercise, and obesity tweets. Using a sequential explanatory mixed-method design for our analytical framework, we analyzed a data corpus of 1.7 million diet, diabetes, exercise, and obesity (DDEO)-related tweets collected over 12 months. Sentiment analysis and topic modeling were used to analyze the data. The results show that overall, 29% of the tweets were positive, and 17% were negative. Using sentiment analysis and latent Dirichlet allocation (LDA) topic modeling, we analyzed 800 positive and negative DDEO topics. From the 800 LDA topics—after the qualitative and computational removal of incoherent topics—473 topics were characterized as coherent. Obesity was the only query health topic with a higher percentage of negative tweets. The use of social media by public health practitioners should focus not only on the dissemination of health information based on the topics discovered but also consider what they can do for the health consumer as a result of the interaction in digital spaces such as social media. Future studies will benefit from using multiclass sentiment analysis methods associated with other novel topic modeling approaches.
Subject
Health Information Management,Health Informatics,Health Policy,Leadership and Management
Reference99 articles.
1. Estimating the Medical Care Costs of Obesity in the United States: Systematic Review, Meta-Analysis, and Empirical Analysis;Value Health,2016
2. Tweet for health: Using an online social network to examine temporal trends in weight loss-related posts;Transl. Behav. Med.,2015
3. Behavioral Science Research in Diabetes: Lifestyle changes related to obesity, eating behavior, and physical activity;Diabetes Care,2001
4. Creswell, J.W. (2014). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches, Sage Publications.
5. The use of social media by state health departments in the US: Analyzing health communication through Facebook;J. Community Health,2016
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献