A survey of social media data analysis for physical activity surveillance
Introduction
Social media technology, such as Twitter, allows users to communicate with each other by sharing short messages and website links. Users often share their thoughts, feelings and opinions on these social media platforms and as a result, social media data could be used to provide real-time monitoring of psychological and behavior outcomes that inform levels of physical activity.1, 2 A unique aspect about social media data from Twitter is that the posts are public and geo-tagged and thus, all Internet users, including health researchers, can readily access this data. Twitter usage has increased 30% from 2012 to 2014.3 Currently 1 in 4 adults uses Twitter and usage is expected to increase steadily in the future.3 Due to the rapid growth in social media use, these sites provide an enormous amount of data (e.g., over 500 million tweets per day on Twitter). The growing body of social media data is becoming a central part of big data research as these data can be modeled alongside other datasets (e.g. biomedical, crime rate) and used to predict outcomes from these datasets. Research has already shown that data from social media technologies can be used for novel approaches to identifying infections disease outbreaks such as influenza transmission4 and HIV outbreaks.5 Methods used to analyze social media data for predicting infectious disease outbreaks could be applied to physical activity research and other fields of study such as forensic science. Currently, no studies have described the application for using social media data to predict and monitor physical activity levels. Therefore, the first part of this paper was to describe current social media analysis approaches (e.g. topic modeling, sentiment analysis and social network analysis) that can be used to monitor and predict levels physical activity in real-time. The second part of this paper aim to discuss ways to apply social media analysis to other fields such as forensic sciences and provide recommendations to further social media research.
Section snippets
Part 1) methods of analyzing social media data for physical activity surveillance
Regular physical activity is associated with important health benefits and it is critical to chronic disease prevention and management.6, 7 Currently, only about 20% adults in the United States meet the recommended amount of physical activity (at least 150 min of moderate-intensity aerobic activity per week8). Based on the latest physical activity survey from Center for Disease Control and Prevention (CDC), the prevalence of physical inactivity varies across the United States.9 The lack of
Part 2) recommendations to advance the field of social media research
Social media-based data have the potential to not only be used as a tool for physical activity surveillance and monitoring, but also be applied to fields such as forensic science. For example, using topic modeling, geo-tagged tweets, and sentiment analysis, social media data may be used to build tools to monitor and predict crime rates, and drug trafficking activates with in a region. Analyzing social media data may help identify individuals who are victims of violence. This may be done by
Conclusion
Surveillance and monitoring of changes in people's behavior and outcomes can help inform government agencies and organizations mobilize appropriate interventions. Social media data has the potential to provide real-time surveillance and prediction of physical activity levels. Current social media analyses approaches that could be used to monitor and predict physical activity levels in real-time include topic modeling, sentiment analysis and network analysis. These approaches can also be applied
Conflicts of interest
None.
References (29)
- et al.
Methods of using real-time social media technologies for detection and remote monitoring of HIV outcomes
Prev Med
(2014 Jun) - et al.
Feasibility of using social networking technologies for health research among men who have sex with men: a mixed methods study
Am J Mens Health
(2014 Jan) - et al.
You are what you tweet: connecting the geographic variation in America's obesity rate to twitter content
PLoS One
(2015) Pew Research Center's Internet & American Life Project; 2015
(2015)- et al.
National and local influenza surveillance through Twitter: an analysis of the 2012-2013 influenza epidemic
PLoS One
(2013) - et al.
Health benefits of physical activity: the evidence
CMAJ
(2006 Mar 14) - et al.
Physical activity and public health: updated recommendation for adults from the american College of Sports medicine and the american heart association
Med Sci Sports Exerc
(2007 Aug) Physical Activity Guidelines Advisory Committee Report
(2008)Facts about Physical Activity
(April 8, 2016)- et al.
Changes in physical activity patterns in the United States, by sex and cross-sectional age
Med Sci Sports Exerc
(2000 Sep)