Research of Distinctibility of Digital Traces in Various Groups of Schoolchildren on the Territory of Altai Region
The use of digital traces of users of social networks in various studies has gained great popularity with the development of methods for analyzing big data. When processing data from social networks, the problem of incomplete information provided by users arises. In this regard, the need to develop an algorithm for restoring information in the digital traces of users of social networks arises. This was the goal of the project. The study of the distinguishability of digital traces was carried out on data from the «VKontakte» social network for students in grades 9 and 11 and their peers, which were divided into four groups. Analysis of subscriptions on unique communities revealed significant differences in groups. Then, based on gradient boosting, an algorithm was built that allows to restore missing information (class or type of educational institution) in the digital traces of adolescents. The algorithm was used to automatically identify groups of schoolchildrenwith incomplete information in a digital traces. Optimization of this algorithm by parameters allows to obtain the precision of the trained model of the order of 0.6. The practical significance of the project is to expand the target audience of future university entrants.