Studying Physical Activity Using Social Media: An Analysis of the Added Value of RunKeeper Tweets

Studying Physical Activity Using Social Media: An Analysis of the Added Value of RunKeeper Tweets

Jeroen Stragier (Ghent University, Ghent, Belgium), Peter Mechant (iMinds, & Department of Communication Studies, Ghent University, Ghent, Belgium) and Lieven De Marez (iMinds, & Department of Communication Studies, Ghent University, Ghent, Belgium)
DOI: 10.4018/ijicst.2013070102
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Smartphones and mobile fitness applications or apps have brought a new experience to physical activities such as running, walking, and cycling. Increased sharing of these activities by users of social networking sites affords the collection of large physical activity datasets. This study assesses to what extent raw data from mobile fitness applications (MFAs) posted on Twitter can be used for studying physical activity and what added value they can provide. A total of 22,258 tweets collected over a nine-month period using RunKeeper mobile fitness app were analyzed. A quantitative analysis of the entire data set and a content analysis of a subset of 2,868 tweets were performed. The data from MFAs exchanged via Twitter provided rich information on various aspects of physical activity including timing and distance of runs, bicycle rides, and walks. Personal reflections shared by RunKeeper users contained additional details on how the activity was experienced. Although further research is needed to determine the representativeness and generalizability of such data, the results of this study may indicate an important direction for extending current methodological practices in physical activity research.
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Research Methods In Physical Activity

A review of the relevant literature indicates the existence of a wide range of research methods and data collection techniques that are applied to the study of physical activity. Among them, self-reporting methods, observational methods, and the use of objective measurement devices are among the most common (Strath et al., 2013; Thomas, Nelson, & Silverman, 2010). A combination of these methods is often used.

Self-reporting methods, as the name indicates, rely on research participants to provide accurate responses to questions regarding behavior or attitudes. Self-reporting methods such as quantitative surveys, for example, International Physical Activity Questionnaire (IPAQ) can afford relatively fast, low-cost, and large scale data collection (Booth, Ainsworth, & Pratt, 2003; Hagstromer, Oja, & Sjostrom, 2006; Hallal & Victora, 2004; van Poppel, Chinapaw, Mokkink, Van Mechelen, & Terwee, 2010). The accuracy and trustworthiness of the responses, however, can be an issue due to reliance on the research participant’s memory (Trost, Pate, Freedson, Sallis, & Taylor, 2000; Prince et al., 2008), potentially socially desirable answers (Shephard, 2003). Various standardized physical activity questionnaires exist, of which IPAQ is commonly used (Booth, Ainsworth, & Pratt, 2003).

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