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Analysis of Students Educational Interests Using Social Networks Data

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Analysis of Images, Social Networks and Texts (AIST 2019)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11832))

Abstract

The paper presents an approach to analyze the structure of students educational interests based on data from social networks (subscriptions to pages and groups in the popular Russian social network Vkontakte). We collected data for 1379 students of Ural Federal University, who study at three institutes of the university. The students were clustered based on their interests in the social network and the clusters were compared with the institutes where students study. The approach allowed us to successfully separate the students who are interested in Computer Science and Humanitarian and Social Science. However, the students who study Economics and Management were not clustered successfully due to the heterogeneity of their interests. The approach could be used not only to determine the educational interests of existing students but also to recommend the most suitable educational area for prospective students based on social networks data.

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Author information

Authors and Affiliations

  1. Ural Federal University, Ekaterinburg, Russia

    Evgeny Komotskiy, Tatiana Oreshkina, Liubov Zabokritskaya, Marina Medvedeva, Andrey Sozykin & Nikolay Khlebnikov

  2. Krasovskii Institute of Mathematics and Mechanics, Ekaterinburg, Russia

    Andrey Sozykin

Authors
  1. Evgeny Komotskiy
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  2. Tatiana Oreshkina
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  3. Liubov Zabokritskaya
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  4. Marina Medvedeva
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  5. Andrey Sozykin
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  6. Nikolay Khlebnikov
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Corresponding author

Correspondence to Evgeny Komotskiy .

Editor information

Editors and Affiliations

  1. RWTH Aachen University, Aachen, Germany

    Wil M. P. van der Aalst

  2. University of Ljubljana, Ljubljana, Slovenia

    Vladimir Batagelj

  3. National Research University Higher School of Economics, Moscow, Russia

    Dmitry I. Ignatov

  4. Krasovskii Institute of Mathematics and Mechanics, Yekaterinburg, Russia

    Michael Khachay

  5. National Research University Higher School of Economics, Moscow, Russia

    Valentina Kuskova

  6. University of Oslo, Oslo, Norway

    Andrey Kutuzov

  7. National Research University Higher School of Economics, Moscow, Russia

    Sergei O. Kuznetsov

  8. National Research University Higher School of Economics, Moscow, Russia

    Irina A. Lomazova

  9. Lomonosov Moscow State University, Moscow, Russia

    Natalia Loukachevitch

  10. LORIA, Vandœuvre-lès-Nancy, France

    Amedeo Napoli

  11. University of Florida, Gainesville, FL, USA

    Panos M. Pardalos

  12. Ca Foscari University of Venice, Venice, Italy

    Marcello Pelillo

  13. National Research University Higher School of Economics, Nizhny Novgorod, Russia

    Andrey V. Savchenko

  14. Kazan Federal University, Kazan, Russia

    Elena Tutubalina

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Komotskiy, E., Oreshkina, T., Zabokritskaya, L., Medvedeva, M., Sozykin, A., Khlebnikov, N. (2019). Analysis of Students Educational Interests Using Social Networks Data. In: van der Aalst, W., et al. Analysis of Images, Social Networks and Texts. AIST 2019. Lecture Notes in Computer Science(), vol 11832. Springer, Cham. https://doi.org/10.1007/978-3-030-37334-4_23

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  • DOI: https://doi.org/10.1007/978-3-030-37334-4_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-37333-7

  • Online ISBN: 978-3-030-37334-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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