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Linking Friends in Social Networks Using HashTag Attributes

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Analysis of Images, Social Networks and Texts (AIST 2020)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12602))

Abstract

Social networks are an integral part of modern life. They allow us to communicate online and exchange all kinds of information. In this paper, we consider the social network Instagram and its hashtags as a key tool for finding relevant information and new friends. The aim of our work is an empirical analysis of hashtags for posts in Instagram with certain locations. We obtain database of users of the Instagram network and collect a dataset of posts for three Far Eastern cities. Then, we build a friendship graph, for which we solve the link prediction problem. We show that both, structural and attributive graph information, such as hashtags, is important to achieve best quality.

O. Gerasimova—The article was prepared within the framework of the HSE University Basic Research Program.

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Notes

  1. 1.

    https://www.instagram.com/.

  2. 2.

    https://twitter.com.

  3. 3.

    https://gephi.org.

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Author information

Authors and Affiliations

  1. HSE University, Moscow, Russia

    Olga Gerasimova & Viktoriia Syomochkina

Authors
  1. Olga Gerasimova
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  2. Viktoriia Syomochkina
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Corresponding author

Correspondence to Olga Gerasimova .

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, St. Petersburg, Russia

    Olessia Koltsova

  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. Moscow State University, Moscow, Russia

    Natalia Loukachevitch

  10. LORIA, Vandœuvre lès Nancy, France

    Amedeo Napoli

  11. Skolkovo Institute of Science and Technology, Moscow, Russia

    Alexander Panchenko

  12. University of Florida, Gainesville, FL, USA

    Panos M. Pardalos

  13. Università Ca' Foscari Venezia, Venice, Italy

    Marcello Pelillo

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

    Andrey V. Savchenko

  15. Kazan Federal University, Kazan, Russia

    Elena Tutubalina

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Gerasimova, O., Syomochkina, V. (2021). Linking Friends in Social Networks Using HashTag Attributes. In: van der Aalst, W.M.P., et al. Analysis of Images, Social Networks and Texts. AIST 2020. Lecture Notes in Computer Science(), vol 12602. Springer, Cham. https://doi.org/10.1007/978-3-030-72610-2_20

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  • DOI: https://doi.org/10.1007/978-3-030-72610-2_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-72609-6

  • Online ISBN: 978-3-030-72610-2

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