Vladislav V. Malakhov

The research aims to analyze the possibilities of using a digital footprint to reveal the identification signs of a person’s professionalization in the field of education (pedagogy) based on big data technologies through social and search networks. The author identifies the reasons for using social and search networks to develop career guidance practices with schoolchildren. The research presents and analyses data about users of accumulated social networks (e.g. Facebook) and search networks (e.g. Yandex and Google). The author shows possible options for clustering user data in the Vkontakte social network with differentiation of user interests and third-party segmentation determined using neural network algorithms (one of the fundamental technologies of big data), based on a variety of different actions of the user of the social network inside and outside the Internet field. The author proposes a variant of a comparative analysis of user interests confirmed by a third-party segment between a group of people from the pedagogical community and a group of professionals from other fields. The hypothesis about the identity of the pool of interests of the pedagogical community is formulated and tested; their pattern is revealed and projected on the graduates of pedagogical specialties of the Tomsk State Pedagogical College in 2022, working in the specialty. Possible variants of the development of the proposed model of clustering the interests of the pedagogical community and extrapolation of the principles of work to different levels of pedagogical education are shown. The research materials are prepared based on the use of the following methods: theoretical and structural analysis, structural-semiotic analysis, and predictive analytics and simulation modeling based on neural network data.