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Model for Assessing the Need to Involve Users of Social Networks in a Healthy Lifestyle and Giving up Bad Habits According to the Data of a Social Network

P. 239–252.
Varnavsky A.

An urgent task is to preserve and maintain the health of the country’s population, including through the promotion of a healthy lifestyle. Since social networks are very popular, especially among young people, it is possible to promote a healthy lifestyle on their basis. Despite the existing research on the influence of social networks on user behaviour, especially to alcohol consumption and smoking, no models are providing personalized recommendations for the user to involve in a healthy lifestyle and quit bad habits. The work aimed to research the young people’s social networks usage indicators and behaviour to a healthy lifestyle and the construction of personalized models to assess the need to change user behaviour. To achieve the aim, experimental research was conducted based on a survey of young people and an assessment of their profiles in social networks. An assessment and analysis of the existence of relationships between indicators of self-assessment of health, the presence of diseases, behaviour to a healthy lifestyle and the behaviour of users in social networks were completed. It was found that self-assessment of health and the presence of chronic diseases are not only interconnected with indicators of behaviour to a healthy lifestyle but also interrelated with respondents’ behaviour indicators in social networks. The theory of cognitive processes and cognitive load can explain these relationships. Based on the presence of interrelationships, regression models were built predicting users’ behaviour to a healthy lifestyle. Using such models embedding in social networks will allow issuing personalized recommendations.

Language: English
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Keywords: здоровый образ жизнисоциальная сетьhealthy lifestylesocial networkмодель прогнозированияPrediction ModelUser BehaviourПоведение пользователя

In book

26th International Conference, DAMDID/RCDL 2024, Nizhny Novgorod, Russia, October 23–25, 2024, Revised Selected Papers. Data Analytics and Management in Data Intensive Domains. (CCIS, volume 2641)
Springer, 2026.
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