Abstract:

Educational globalization makes leading universities search for new ways of recruitment aimed at gifted smart youth not only from the same but from other countries as well. Since the university resources are limited from the point of view of coverage and attraction of the entrants, there is a need for a focused informational influence on a precise audience with specific features. This audience consists of high school students who show some interest in certain academic subjects and have soft skills for a successful study and an academic career. At the same time, the “natural habitat” of the modern schoolchildren is social networks. These social networks are the source of open data basing on which one can define potential entrants with a set of the required features according to the university entrant model. These data analysis and interpretation let a university to find promising entrants in any region or even a country and establish a direct communication with them via the social networks without any mediators.

The current paper covers the experience in collecting and analyzing the data about the users of social networks (the Russian social network VKontakte is taken as an example) to define the potential entrants. The authors provide a solution to the tasks related to building an entrant model, exporting data from the social networks using API, processing natural language, defining the entrants’ soft skills and educational interest via the analysis of the data taken from their profile, their walls, their friendship connections.

Keywords:

Social Media, data analysis, big data, natural language processing, attract entrants.