Outdoor fitness activity under COVID-19 restrictions. Wearable devices, images, and posts as sources of information on users

Abstract

Our study aimed to present amateur sports models during the CO VID-19 restrictions on outdoor activities. We used mixed research methods: the questionnaire research data and information available through wearable devices. We investigate physical activity phenomena based on questionnaire results and existing data from a popular social networking site. Firstly, we asked respondents about their training types, rhythm, and preferences in using new technologies (wearables devices and social networks to upload and share results) in individual physical activity practices. Secondly, we also used a collection of over 11 thousand photos of 3138 users, with metadata downloaded from Instagram to compare declarations and content. The obtained data were processed using machine learning and Python software. Analyzing the results, we showed a change in the intensity of practicing three selected types of activity. We also analyzed the data set (photos, tags, and metadata) from a social network. The conclusions show the potential of triangulation of methods and data to describe the amateur physical activity and the change of these practices during CO VID-19 limitations in indoor and outdoor sports.