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A Data Model of the Internet Social Environment

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Advances in Artificial Systems for Medicine and Education II (AIMEE2018 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 902))

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Abstract

In the chapter, there was made a conceptual chart of the Internet social environment platform. It was developed the following models: a data model, a service model, a navigation model, a presentation model, and a visual model. The Internet social environment platform’s data was divided into four groups according to such categories: content, frequency of changes, distribution statues, and owner. In the chapter, the process of data transformation from a visual model till a data model was analyzed. It was also highlighted key nodes page of the users platform and made their detailed analysis. The basic principles of formation and preservation of nodes of these platforms are analyzed. A comparative analysis of the presence of key nodes of the most common virtual community’s platforms has been made. The Internet social environment, which is most suitable for the analysis, is established.

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Authors and Affiliations

  1. Social Communications and Information Activities Department, Lviv Polytechnic National University, Lviv, Ukraine

    Andriy Peleshchyshyn & Oleg Mastykash

Authors
  1. Andriy Peleshchyshyn
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  2. Oleg Mastykash
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Corresponding author

Correspondence to Oleg Mastykash .

Editor information

Editors and Affiliations

  1. School of Educational Information Technology, Central China Normal University, Wuhan, Hubei, China

    Zhengbing Hu

  2. Mechanical Engineering Research Institute, Russian Academy of Sciences, Moscow, Russia

    Sergey V. Petoukhov

  3. Halmos College of Natural Sciences and Oceanography, Nova Southeastern University, Davie, FL, USA

    Matthew He

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Peleshchyshyn, A., Mastykash, O. (2020). A Data Model of the Internet Social Environment. In: Hu, Z., Petoukhov, S., He, M. (eds) Advances in Artificial Systems for Medicine and Education II. AIMEE2018 2018. Advances in Intelligent Systems and Computing, vol 902. Springer, Cham. https://doi.org/10.1007/978-3-030-12082-5_40

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