Interval model of the portrait of users of the thematic group on environmental issues in the social network

Authors

  • M.P. Divak West Ukrainian National University
  • A.M. Melnyk West Ukrainian National University
  • Ye.S. Kedrin West Ukrainian National University
  • Frank Avalon Otoo West Ukrainian National University

DOI:

https://doi.org/10.31649/1681-7893-2021-41-1-78-88

Keywords:

interval model, information message, web resource, portrait of users, social network

Abstract

Mathematical models of dynamics of efficiency of information social networks are considered in the work. An approach to estimating model parameters is proposed. A number of experimental studies were conducted on the basis of data on the functioning of a special online group Facebook. The indicator of the characteristics of the information message was studied. An interval discrete model in the form of a difference equation is obtained, which describes the dynamics of users' reactions to messages in thematic groups of social networks. On the basis of the conducted experiments, the efficiency of application of the offered model is confirmed

Author Biographies

M.P. Divak, West Ukrainian National University

д.т.н., професор

A.M. Melnyk, West Ukrainian National University

к.т.н., доцент

Ye.S. Kedrin, West Ukrainian National University

аспірант

Frank Avalon Otoo, West Ukrainian National University

аспірант

References

A. Kovbasistyi, A. Melnyk, M. Dyvak, V. Brych and I. Spivak, "Method for detection of non-relevant and wrong information based on content analysis of web resources," 2017 XIIIth International Conference on Perspective Technologies and Methods in MEMS Design (MEMSTECH), 2017, pp. 154-156, doi: 10.1109/MEMSTECH.2017.7937555.

Z. Zhao, "The containment of fake news propagation in online social networks," 2020 IEEE International Conference on Information Technology,Big Data and Artificial Intelligence (ICIBA), 2020, pp. 387-391, doi: 10.1109/ICIBA50161.2020.9276936.

L. Tuanhua, "Interactive Behavior Analysis Based on Social Network," 2021 International Conference of Social Computing and Digital Economy (ICSCDE), 2021, pp. 188-191.

J. Hu, M. Liu and J. Zhang, "A semantic model for academic social network analysis," 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014), 2014, pp. 310-313, doi: 10.1109/ASONAM.2014.6921602.

D. Zhu, B. Zhu, T. Huang and Y. Li, "Multi-attribute Multi-Task Online Assignment Algorithm Based on Social Network," 2020 IEEE 6th International Conference on Computer and Communications (ICCC), 2020, pp. 753-757, doi: 10.1109/ICCC51575.2020.9344924.

Dipraj, S. Vishwakarma and J. Singh, "Social Internet of Things: The collaboration of Social Network and Internet of Things and its Future," 2020 2nd International Conference on Advances in Computing, Communication Control and Networking (ICACCCN), 2020, pp. 535-539, doi: 10.1109/ICACCCN51052.2020.9362847.

M. Wang, Q. Li and Y. Lin, "A personalized search model using online social network data based on a holonic multiagent system," in China Communications, vol. 17, no. 2, pp. 176-205, Feb. 2020.

C. Laghridat, I. Mounir and M. Essalih, "Analyzing Friendship's Social Networks Using The Topological Indices," 2019 International Conference on Wireless Networks and Mobile Communications (WINCOM), 2019, pp. 1-5.

Hernes, M., Nguyen, N.T., Maleszka, M., Bytniewski, A. The automatic summarization of text documents in the cognitive integrated management information system (2015) Proceedings of the 2015 Federated Conference on Computer Science and Information Systems, FedCSIS 2015, art. no. 2015F188, pp. 1387-1396.

Rot, A., Kutera, R., Gryncewicz, W. Design and assessment of user interface optimized for elderly people. A case study of actgo-gate platform (2017) ICT4AWE 2017 - Proceedings of the 3rd International Conference on Information and Communication Technologies for Ageing Well and e-Health, pp. 157-163.

Severiukhina O., Bochenina K. Segment-wise Users' Response Prediction based on Activity Traces in Online Social Networks // 2019 6th International Conference on Social Networks Analysis, Management and Security, SNAMS 2019 - 2019, pp. 291- 296

Severiukhina O., Bochenina K., Kesarev S., Boukhanovsky A. Parallel data-driven modeling of information spread in social networks // Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) - 2018, Vol. 10860, pp. 247-259

Chomiak-Orsa, I., Rot, A., Blaicke, B. Artificial Intelligence in Cybersecurity: The Use of AI Along the Cyber Kill Chain (2019) Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11684 LNAI, pp. 406-416.

Hernes, M. Performance evaluation of the customer relationship management agent's in a cognitive integrated management support system (2015) Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9240 LNCS, art. no. A5, pp. 86-104.

Hernes, M. Consensus Theory for Cognitive Agents' Unstructured Knowledge Conflicts Resolving in Management Information Systems (2019) Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11370 LNCS, pp. 1-119

Rot, A. Selected issues of IT risk management in the cloud computing model. Theory and practice (2017) IMCIC 2017 - 8th nternational Multi-Conference on Complexity, Informatics and Cybernetics, Proceedings, 2017-March, pp. 89-94.

S. Castelo, T. Almeida, A. Elghafari, A. Santos, K. Pham, E. Nakamura, and J. Freire. 2019. A Topic-Agnostic Approach for Identifying Fake News Pages. In Companion Proceedings of The 2019 World Wide Web Conference. ACM, 975–980

E. Lucas, and P. Pomeranzev, Winning the Information War: Techniques and counter-strategies to Russian propaganda in Central and Eastern Europe, Washington, D.C.: Center for European Policy Analysis, 2016.

Duran, G.; Valero, J.; Amigó, J.M.; Giménez, Á.; Martinez-Bonastre, O. Bifurcation analysis for the Internet congestion. In Proceedings of the IEEE INFOCOM 2019—IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), Paris, France, 29 April–2 May 2019; pp. 1073–1074.

V. D. Oliseenko and T. V. Tulupyeva, "Neural Network Approach in the Task of Multi-label Classification of User Posts in Online Social Networks," 2021 XXIV International Conference on Soft Computing and Measurements (SCM), 2021, pp. 46-48, doi: 10.1109/SCM52931.2021.9507148.

Dyvak, M., Papa, O., Melnyk, A., Pukas, A., Porplytsya, N., Rot, A. Interval model of the efficiency of the functioning of information web resources for services on ecological expertise (2020) Mathematics, 8 (12), art. no. 2116, pp. 1-12.

Dyvak, M., Stakhiv, P., Pukas, A. Algorithms of parallel calculations in task of tolerance ellipsoidal estimation of interval model parameters (2012) Bulletin of the Polish Academy of Sciences: Technical Sciences, 60 (1), pp. 159-164.

M. Dyvak, N. Porplytsya, I. Borivets and M. Shynkaryk, "Improving the computational implementation of the parametric identification method for interval discrete dynamic models," 2017 12th International Scientific and Technical Conference on Computer Sciences and Information Technologies (CSIT), 2017, pp. 533-536, doi: 10.1109/STC-CSIT.2017.8098844.

M. Dyvak, "Parameters Identification Method of Interval Discrete Dynamic Models of Air Pollution Based on Artificial Bee Colony Algorithm," 2020 10th International Conference on Advanced Computer Information Technologies (ACIT), 2020, pp. 130-135, doi: 10.1109/ACIT49673.2020.9208972.

Karaboga, D.; Kaya, E. Estimation of number of foreign visitors with ANFIS by using ABC algorithm. Soft Comput. 2019, 24, 7579–7591.

Karaboga, D. An Idea Based on Honey Bee Swarm for Numerical Optimization, Technical Report—TR06; Technical Report; Erciyes University: Kayseri, Turkey, 2005.

Karaboga, D.; Basturk, B. A powerful and efficient algorithm for numerical function optimization: Artificial bee colony (ABC) algorithm. J. Glob. Optim. 2007, 39, 459–471.

Downloads

Abstract views: 164

Published

2022-05-02

How to Cite

[1]
M. Divak, A. Melnyk, Y. Kedrin, and F. A. Otoo, “Interval model of the portrait of users of the thematic group on environmental issues in the social network”, Опт-ел. інф-енерг. техн., vol. 41, no. 1, pp. 78–88, May 2022.

Issue

Vol. 41 No. 1 (2021)

Section

Optical And Optical-Electronic Sensors And Converters In Control And Environmental Monitoring Systems

Metrics

Downloads

Download data is not yet available.

License

Автори, які публікуються у цьому журналі, погоджуються з наступними умовами:

  1. Автори залишають за собою право на авторство своєї роботи та передають журналу право першої публікації цієї роботи на умовах ліцензії Creative Commons Attribution License, котра дозволяє іншим особам вільно розповсюджувати опубліковану роботу з обов'язковим посиланням на авторів оригінальної роботи та першу публікацію роботи у цьому журналі.
  2. Автори мають право укладати самостійні додаткові угоди щодо неексклюзивного розповсюдження роботи у тому вигляді, в якому вона була опублікована цим журналом (наприклад, розміщувати роботу в електронному сховищі установи або публікувати у складі монографії), за умови збереження посилання на першу публікацію роботи у цьому журналі.
  3. Політика журналу дозволяє і заохочує розміщення авторами в мережі Інтернет (наприклад, у сховищах установ або на особистих веб-сайтах) рукопису роботи, як до подання цього рукопису до редакції, так і під час його редакційного опрацювання, оскільки це сприяє виникненню продуктивної наукової дискусії та позитивно позначається на оперативності та динаміці цитування опублікованої роботи (див. The Effect of Open Access).