When Fitness Meets Social Networks: Investigating Fitness Tracking and Social Practices on WeRun
Abstract
The last two decades have seen growing interest in promoting physical activities by using self-tracking technologies. Previous work has identified social interactions in self-tracking as a crucial factor in motivating users to exercise. However, it is unclear how integrating fitness features into complex pre-existing social network affects users' fitness tracking practices and social interactions. In this research, we address this gap through a qualitative study of 32 users of WeRun--a fitness plugin of the widely adopted Chinese mobile social networking service WeChat. Our findings indicate that sharing fitness data with pre-existing social networks motivates users to continue self-tracking and enhances their existing social relationships. Nevertheless, users' concerns about their online personal images lead to challenges around privacy. We discuss how our study could advance understanding of the effects of fitness applications built on top of pre-existing social networks. We present implications for future social fitness applications design.
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The growing interest in exercise and sports, as well as the trend of sharing fitness data through social media, may explain why social media content focusing on activities and sports attracts tourists from all segments.
“This may be attributed to the growing interest in exercise and sports, as well as the trend of sharing fitness data through social media [70].”
From Push and Pull Travel Motivation: Segmentation of the Greek Market for Social Media Marketing in Tourism (2020) · cites this paper as [70]
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- Authors
- Gui, X., Chen, Y., Caldeira, C., Xiao, D., & Chen, Y.
- Affiliations
- University of California, Irvine (US)
- Shenzhen Polytechnic University (CN)
- Venue
- Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems
- Publisher
- ACM
- Published
- 2017-05-02
- Pages
- 1647-1659
- OpenAlex
- W2611253299
- Cited by
- 82
- References
- 49
- Citations by year
- 2026: 8 · 2025: 10 · 2024: 11 · 2023: 3 · 2022: 10 · 2021: 13 · 2020: 12 · 2019: 6 · 2018: 6 · 2017: 3
- FWCI
- 5.58
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- CHI Conference on Human Factors in Computing Systems (publishedVersion)
- Funders
- US National Science Foundation (HCC-1219197)
- Swiss National Science Foundation (P2ELP2_158933)
- Topics
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Keywords
- fitness tracking, self-tracking, social networks, exercise motivation, WeChat, privacy concerns, mobile social networking
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