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Assessment of the main features of the model of dissemination of information in social networks

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 13 No. 6 (2023)

DOI
10.11591/ijece.v13i6.pp6729-6736
ISSN
2722-2578, 2088-8708
Published
2023-12-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Social networks provide a fairly wide range of data that allows one way or another to evaluate the effect of the dissemination of information. This article presents the results of a study that describes methods for determining the key parameters of the model needed to analyze and predict the dissemination of information in social networks. An approach based on the analysis of statistical data on user behavior in social networks is proposed. The process of evaluating the main features of the model is described, including the mathematical methods used for data analysis and information dissemination modeling. The study aims to understand the processes of information dissemination in social networks and develop recommendations for the effective use of social networks as a communication and brand promotion tool, as well as to consider the analytical properties of the classical susceptible-infected-removed (SIR) model and evaluate its applicability to the problem of information dissemination. The results of the study can be used to create algorithms and techniques that will effectively manage the process of information dissemination in social networks.

Collaboration network of the authors

18 authors · 65 co-authorship links · 40 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • L. N. Gumilyov Eurasian National University
  • Astana Medical University
  • Astana IT University
  • Binghamton University
  • Karaganda Buketov University
  • S.Seifullin Kazakh Agro Technical University
  • Abylkas Saginov Karaganda Technical University
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Vladimir V. NikulinBinghamton University2
Tansuly ZadenovaL. N. Gumilyov Eurasian National University2
Ali MyrzatayL. N. Gumilyov Eurasian National University2
Gulden MurzabekovaS.Seifullin Kazakh Agro Technical University1
Natalya GlazyrinaL. N. Gumilyov Eurasian National University1
Bakhytgul RysbekkyzyAbylkas Saginov Karaganda Technical University1
Raikhan MuratkhanKaraganda Buketov University1
Serik EslyamovL. N. Gumilyov Eurasian National University1
Nurgul AziyevaAffiliation unknown1
Nazira BaktiyarovaAstana Medical University1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>Assessment of the main features of the model of dissemination of information in social networks</dc:title><dc:creator>Imanberdi, Assel</dc:creator><dc:creator>Lira, La</dc:creator><dc:creator>Aitolkyn, Kulmuratova</dc:creator><dc:creator>Leila, Rzayeva</dc:creator><dc:creator>Abitova, Gulnara</dc:creator><dc:creator>Aigerim, Bakiyeva</dc:creator><dc:creator>Ainur, Orynbayeva</dc:creator><dc:creator>Assem, Baimakhanbetova</dc:creator><dc:description>&lt;jats:p&gt;&amp;lt;span lang="EN-US"&amp;gt;Social networks provide a fairly wide range of data that allows one way or another to evaluate the effect of the dissemination of information. This article presents the results of a study that describes methods for determining the key parameters of the model needed to analyze and predict the dissemination of information in social networks. An approach based on the analysis of statistical data on user behavior in social networks is proposed. The process of evaluating the main features of the model is described, including the mathematical methods used for data analysis and information dissemination modeling. The study aims to understand the processes of information dissemination in social networks and develop recommendations for the effective use of social networks as a communication and brand promotion tool, as well as to consider the analytical properties of the classical susceptible-infected-removed (SIR) model and evaluate its applicability to the problem of information dissemination. The results of the study can be used to create algorithms and techniques that will effectively manage the process of information dissemination in social networks.&amp;lt;/span&amp;gt;&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2023-12-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v13i6.pp6729-6736</dc:identifier><dc:identifier>10.11591/ijece.v13i6.pp6729-6736</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 13 No 6 (2023); 6729</dc:source><dc:source>2722-2578</dc:source><dc:source>2088-8708</dc:source><dc:relation>https://ijece.iaescore.com/index.php/IJECE/article/viewFile/32338/16997</dc:relation><dc:rights>http://creativecommons.org/licenses/by-sa/4.0</dc:rights></oai_dc:dc>