BUSINESS INFORM JOURNAL.

УКР

ENG

Search:

REGISTRATION CERTIFICATE

KV #19905-9705 PR dated 02.04.2013.

FOUNDERS

RESEARCH CENTRE FOR INDUSTRIAL DEVELOPMENT PROBLEMS of NAS (KHARKIV, UKRAINE)

According to the decision No. 802 of the National Council of Television and Radio Broadcasting of Ukraine dated 14.03.2024, is registered as a subject in the field of print media.
ID R30-03156

PUBLISHER

Liburkina L. M.

SITE SECTIONS

Cluster-Analyzing the Use and Spread of Internet Technologies in the Regions of Ukraine
Tumanov O. O.

Tumanov, Oleksii O. (2020) “Cluster-Analyzing the Use and Spread of Internet Technologies in the Regions of Ukraine.” Business Inform 3:244–252.
https://doi.org/10.32983/2222-4459-2020-3-244-252

Section: Economic statistics

Article is written in Ukrainian
Downloads/views: 4

Download article (pdf) -

UDC 303.722.4:[332.132:004](477)

Abstract:
In recent decades, the development and spread of Internet technologies have gained enormous momentum. The use of the mobile Internet has greatly accelerated this process. People no longer need to stay at home or in an office to stay online, and some have even completely moved their work to an online environment. Social network, blogs and mass media are important elements of this environment. Social media quickly gained popularity as it enables people to communicate and share their thoughts. Automated data analysis is important to obtain meaningful information that potential businesses, users, and consumers need. In order to better learn the use of social media, the first necessity is to focus on the overall approach and find reliable indicators. These indicators can be presented by information and communication technologies (ICT) data that impact all aspects of human life. They play a significant role in work, business, education and entertainment. This article includes an overview of the algorithms of common clustering methods and references to the studies carried out in recent years that have used appropriate algorithms: 1) based on division; 2) based on hierarchy; 3) on a hybrid basis and 4) based on density. The use and spread of Internet technologies in the regions of Ukraine are researched. The information base of the research is indicators of the existing ICT infrastructure in the regions of Ukraine as of year 2018. Based on the data on Internet use in the regions of Ukraine, a cluster analysis was conducted and visualization of distribution to the resulted groups was presented.

Keywords: clustering methods, information and communication technologies, analysis, algorithms, research.

Fig.: 4. Tabl.: 2. Bibl.: 17.

Tumanov Oleksii O. – Applicant, Department of Statistics, Accounting and Auditing, V. N. Karazin Kharkiv National University (4 Svobody Square, Kharkіv, 61022, Ukraine)
Email: [email protected]

List of references in article

Riadno, O. A., and Berkut, O. V. “Doslidzhennia struktury ta dynamiky dyferentsiatsii sotsialno-ekonomichnoho rozvytku rehioniv Ukrainy na osnovi klasternoho analizu“ [A Study of the Structure and Dynamics of Differentiation of Social and Economic Development of Ukraine Based on a Cluster Analysis]. Ekonomichnyi visnyk Donbasu. 2016. https://core.ac.uk/download/pdf/87393771.pdf
Merkulova, T. B., and Bohdanova, H. C. “Dovira i sotsialno-ekonomichnyi rozvytok: klasternyi analiz zviazku pokaznykiv“ [Trust and Socio-Economic Development: Cluster Analysis of Parameter Interdependencies]. Visnyk Kharkivskoho natsionalnoho universytetu imeni V. N. Karazina. Seriia «Ekonomichna». 2016. https://periodicals.karazin.ua/economy/article/view/8654/8189
Yerina, A. M. Statystychne modeliuvannia ta prohnozuvannia [Statistical Modeling and Forecasting]. Kyiv: KNEU, 2014.
Korepanov, H. S., Lazebnyk, Yu. O., and Ponomaryova, T. V. “Zastosuvannia klasternoho analizu dlia hrupuvannia rehioniv za rivnem investytsiinoi pryvablyvosti“ [Using Cluster Analysis to Regions Grouping by the Degree of Investment Appeal]. Visnyk Kharkivskoho natsionalnoho universytetu imeni V. N. Karazina. Seriia «Ekonomichna». 2014. https://periodicals.karazin.ua/economy/article/view/5409/4956
Korepanov, O. S., and Stepanov, O. M. “Statystychnyi analiz rynku pratsi v Ukraini metodamy bahatovymirnoi klasyfikatsii: rehionalnyi aspekt“ [Statistical Analysis of the labor Market in Ukraine Using Multidimensional Classification Methods: the Regional Aspect]. Problemy ekonomiky. 2017. https://www.problecon.com/export_pdf/problems-of-economy-2017-4_0-pages-384_392.pdf
Dostup domohospodarstv Ukrainy do internetu u 2018 rotsi (za danymy vybirkovoho obstezhennia umov zhyttia domohospodarstv Ukrainy) : statystychnyi zbirnyk [Access of Households of Ukraine to the Internet in 2018 (According to a Sample Survey of Living Conditions of Households in Ukraine): A Statistical Collection]. Kyiv: Derzhavna sluzhba statystyky Ukrainy, 2019.
Zadeh, L. A., Abbasov, A. M., and Shahbazova, Sh. N. “Analysis of Twitter Hashtags: Fuzzy Clustering Approach“. Fuzzy Information Processing Society (Nafips) Held Jointly with 2015 : 5th World Conference on Soft Computing (WCONSC). IEEE, 2015. DOI: 10.1109/NAFIPS-WConSC.2015.7284196
Anumol, B., and Pattani, R. V. “Efficient Density Based Clustering of Tweets and Sentimental Analysis Based on Segmentation“. International Journal of Computer Techniques. 2016. http://www.ijctjournal.org/Volume3/Issue3/IJCT-V3I3P9.pdf
Baralis, E. et al. “Analysis of Twitter Data Using a MultipleLevel Clustering Strategy“. International Conference on Model and Data Engineering. Springer, 2013. https://link.springer.com/chapter/10.1007/978-3-642-41366-7_2
Vicente, M., Batista, F., and Carvalho, J. P. “Twitter Gender Classification Using User Unstructured Information“. Fuzzy Systems (Fuzz-IEEE) : IEEE International Conference. IEEE, 2015. 1-7. DOI: 10.1109/FUZZ-IEEE.2015.7338102
Ifrim, G., Shi, B., and Brigadir, I. “Event Detection in Twitter Using Aggressive Filtering and Hierarchical Tweet Clustering“. Second Workshop on Social News on the Web (Snow). 2014. http://ceur-ws.org/Vol-1150/ifrim.pdf
“DBSCAN“. Vikipediia. https://uk.wikipedia.org/wiki/DBSCAN
Friedemann, V. “Clustering A Customer Base Using Twitter Data“. 2015. https://pdfs.semanticscholar.org/08cd/1743d71b9f3e54208871c1562c6083b25f24.pdf
“Global Digital Report 2019 - We are Social“. https://wearesocial.com/global-digital-report-2019
Li, C. et al. Tweet Segmentation and Its Application to Named Entity Recognition, 2015. DOI: 10.1109/TKDE.2014.2327042
Kaur, N. “A Combinatorial Tweet Clustering Methodology Utilizing Inter and Intra Cosine Similarity“. Regina, 2015. https://ourspace.uregina.ca/bitstream/handle/10294/6549/Kaur_Navneet_200331665_MASC_SSE_Fall2015.pdf?sequence=1
Soni, R., and Mathai, K. J. “Improved Twitter Sentiment Prediction Through Cluster-Then-Predict Model“. International Journal of Computer Science and Network. 2015. https://arxiv.org/ftp/arxiv/papers/1509/1509.02437.pdf

FOR AUTHORS

License Contract

Conditions of Publication

Article Requirements

Regulations on Peer-Reviewing

Publication Contract

Current Issue

Frequently asked questions

INFORMATION

The Plan of Scientific Conferences

OUR PARTNERS

Journal «The Problems of Economy»

The site and its metadata are licensed under CC BY-SA.

Write to webmaster