Detection of social media users who lead a healthy lifestyle

Public healthcare is a big priority for society. The ability to diagnose and monitor various aspects of public health through social networks is one of the new problems that are of interest to researchers. In this paper, we consider the task of automatically classifying people who lead a healthy lifestyle and users who do not lead a healthy lifestyle by processing text messages and other profile information from the Russian-speaking social network VKontakte. We describe the process of extracting relevant data from user profiles for our dataset. We evaluate several machine learning methods and report experimental results. The best performance in our experiments was achieved by the model that was trained on a combination of N-gram features retrieved from user original posts and reposts. © Springer Nature Switzerland AG 2020.

Авторы
Khalil K. 1 , Stankevich M. 2 , Smirnov I. 1, 2 , Danina M.3
Язык
Английский
Страницы
240-250
Статус
Опубликовано
Том
12412 LNAI
Год
2020
Организации
  • 1 Peoples’ Friendship University of Russia (RUDN University), Moscow, Russian Federation
  • 2 Federal Research Center Computer Science and Control of RAS, Moscow, Russian Federation
  • 3 Psychological Institute of Russian Academy of Education, Moscow, Russian Federation
Ключевые слова
Classification; Healthy lifestyle; Social networks
Дата создания
02.11.2020
Дата изменения
02.11.2020
Постоянная ссылка
https://repository.rudn.ru/ru/records/article/record/65466/