Healthy behavior with social apps: Proposal for evolution study of the use of fitness social apps on Facebook

Paschoal, Fabio; Ebecken, Nelson F. F.; Ribeiro, Gabriel Vinicius Silva; Daquer, Leandro Moniz de Aragão; Ogasawara, Eduardo

doi:10.1109/cisti.2016.7521484

Cited by 2 publications

(3 citation statements)

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“…1 These interactions allow researchers to observe the behavior of users, 2 including the motivation or influence that they can have on other people regarding behavioral changes. 3 Facebook has many users and currently is the largest OSN. 4 Online socialization is increasing and becoming more and more intense, with positive or negative reactions and emotional contagion.…”

Section: Introductionmentioning

confidence: 99%

“…10 Thus, the aim of this study was to develop a framework capable of monitoring and enabling the analysis of users' behavior on Facebook, 11 who use these type of technology, in order to define their Standard Behavior Pattern. 3,8,9,12,13 This analysis was carried out by monitoring the practice of shared physical activities on social media. For this, we developed FitRank, an app integrated with Facebook, which extracts the information for monitoring.…”

Section: Introductionmentioning

confidence: 99%

“…5 Sharing physical activity rankings is a good example, since they help to improve the quality of life. 3,9,13 Moreover, with its dissemination, it is expected that FitRank may become a support tool for combating sedentary lifestyle. It may act as a motivator for the practice of physical 10 activities, which can reduce the costs of public and private health systems, considering the diseases related to a sedentary lifestyle.…”

Section: Introductionmentioning

confidence: 99%

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Physical Activity Level of Facebook Users

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et al. 2020

Rev Bras Med Esporte

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Introduction: Interactions of Facebook users led to a study of the influence that users can exert on behavioral changes for a healthier life. Objective: To analyze the behavior of Facebook users in order to define the Users' Behavioral Patterns, by monitoring the practice of physical activities shared online, aided by a social competition among users, with the aim of combating sedentarism through the modern attraction of technology and gamification. Methods: A computational tool was developed to extract data from physical activity shared online. The tool, named FitRank, has permissions to access users' data. Tables and classifications were generated based on an analysis of the data in the database, using decision tree algorithms and descriptive statistical analysis. Results: users were classified according to sociodemographic data, and data on the creation of competitive rankings and the practice of physical activities, including the definition of the User's Behavioral Pattern. Conclusion: The study suggested the importance of technological innovations to combat sedentarism, in line with current social entertainment technologies to make them more enjoyable and motivating for the regular practice of physical activities and to provide a better quality of life. Level of Evidence II; Retrospective study.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%