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FitRank — Social app to combat physical inactivity study of the use of fitness social apps on Facebook's users profiles

机译:FitRank —社交应用程序,用于对抗在Facebook用户个人资料上使用健身社交应用程序而导致的身体不活跃的研究

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Social Applications (SA) work in an integrated way with the Online Social Networks (OSN) and allow both the creation of rich contents to share in the OSN as well as the extraction and mining of the data shared in the OSN. This work presents FitRank SA, which creates customizable rankings of shared physical activity on Facebook, with the possibility of up to 60 variations of rankings types. It extracts the data of activities shared by most SA physical activity monitoring, as well as allows the user to share their rankings in their Facebook profile. Their innovation is to group in a same ranking users of eleven SA physical activity monitoring, allowing a greater socialization among them and a greater motivation to practice sports and combat sedentary lifestyle, stimulating its users to a change of behavior for a life healthier. FitRank works with the concept of gamification like a social competition for healthy behavior. It is an integral part of an ongoing PhD thesis that will mining extracted data to compose the Behavioral User Pattern (BUP) in relation to its practice of physical activities, such as the goal of correlating healthy habits with practice of physical activities, in addition to predict the healthy behavior of the user, with the motivation of using Facebook. In this paper, the preliminary results of the use of FitRank, with sociodemographic information and also the execution of physical activities by its users, are presented.
机译:社交应用程序(SA)与在线社交网络(OSN)集成在一起工作,并允许创建要在OSN中共享的丰富内容以及提取和挖掘在OSN中共享的数据。这项工作介绍了FitRank SA,该公司可以在Facebook上创建共享体育活动的可自定义排名,并可能有多达60种排名类型的变化。它提取大多数SA体育活动监控共享的活动数据,并允许用户在其Facebook个人资料中共享其排名。他们的创新是将11种SA体育活动监控的用户分组,以排名相同的方式进行,从而使他们之间的社交活动更加活跃,并有更大的运动习惯和打击久坐不动的生活方式的动机,从而刺激其用户改变行为习惯,从而使他们的生活更健康。 FitRank采用游戏化的概念,就像是​​一场针对健康行为的社会竞赛。它是正在进行的博士学位论文不可或缺的一部分,该论文将挖掘提取的数据以构成与体育锻炼相关的行为用户模式(BUP),例如将健康习惯与体育锻炼相关联的目标。通过使用Facebook的动机来预测用户的健康行为。本文介绍了使用FitRank的初步结果,以及社会人口统计信息以及用户执行的体育活动。

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