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            Pompilos, a Model for Augmenting Health Assistant Applications with Social Media Content
            
            
               Henrique Damasceno Vianna (University of Vale do Rio do Sinos, Brazil)  
              
             
            
            
               Jorge Luis Victória Barbosa (University of Vale do Rio do Sinos, Brazil)  
              
             
                    
            
              Abstract: Caused by habits such as poor diets, lack of   physical activity practice or smoking, non-communicable diseases   were elected by the World Health Organization as one of the greatest   challenges of the twenty-first century, despite a lot of information   produced in social media focused on preventing this type of   disease. This paper presents the Pompilos Model, which aims at   improving computer-aided social support by suggesting beneficial   health resources and revealing what inuences other people's health,   so to foster better health behaviors in social relations. In order   to evaluate the model's feasibility, we performed a random   experiment during one month and half with two groups to assess the   influence of messages related to the prevention of chronic   diseases. Those messages presented information on a healthier diet,   the practice of physical activities, and ways to lose weight, from   monitored Twitter profiles on the habits of health assistant web   application's users. So it would be possible to manage food intake,   the practice of physical activities, and weight control. Messages   related to the prevention of chronic diseases, such as a healthier   diet, the practice of physical activities, and weight loss from   monitored Twitter profiles were directed to an intervention group as   a way to re-engage users in their care activities. With this   information, we found a correlation between message reading and the   access to the application history feature among intervention   users. 
             
            
              Keywords: architecture for distributed systems, noncommunicable diseases prevention, social network analysis 
             
            Categories: H.3.4, H.3.5, J.4  
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