The Research of Cluster Analysis Ways of Application for Business Promotion in Social Networks

Шевченко, Світлана Миколаївна and Жданова, Юлія Дмитрівна and Шевцова, Т.І. (2023) The Research of Cluster Analysis Ways of Application for Business Promotion in Social Networks Вісник Херсонського національного технічного університету (4(87)). pp. 271-281. ISSN 2078 – 4481

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Abstract

The use of social networks to achieve business goals, in particular to promote one's services (goods), is in demand in today's world. In 2022, more than 4.59 billion people (Statista) used social networks. Given such a colossal audience of active users, marketers consider it important and meaningful to use social networks for their company's business activities. Studying methods and tools to promote products on the Internet is a result of this. The review of scientific and methodical literature has highlighted existing methods of business promotion: Owned Media; Paid Media; Earned Media; Social Media, the main drawback of which are negative comments from users, which harms the company’s reputation. This article considers the possibility of applying methods of cluster analysis to promote business in social networks. The concept of cluster analysis has been defined, the most popular methods of cluster analysis have been described, a typical mechanism for its implementation has been presented. The study is based on block-schemes of clustering by near neighbor method and k-means method. Advantages and disadvantages have been identified in each of them. As an example, the distribution of consumers of services of «EPAM SYSTEMZ» LLC, which is provided for a day, depending on the demand for services of the company, taking into account the age criterion. The results showed which services and for what age are more attractive, which will help to more effectively carry out measures to stimulate sales of IT services in social networks, which will lead to an increase in the volume of profit of the organization in the future. The results of the study can be introduced into the educational process of students of economic profile and students of branch of knowledge 12 Information Technologies.

Item Type:	Article
Uncontrolled Keywords:	social networks; promotion system; needs of service consumers; cluster analysis; nearest neighbor algorithm; k-means algorithm
Subjects:	Це архівна тематика Київського університету імені Бориса Грінченка > Статті у наукометричних базах > Index Copernicus Це архівна тематика Київського університету імені Бориса Грінченка > Статті у журналах > Фахові (входять до переліку фахових, затверджений МОН)
Divisions:	Це архівні підрозділи Київського університету імені Бориса Грінченка > Факультет інформаційних технологій та математики > Кафедра інформаційної та кібернетичної безпеки імені професора Володимира Бурячка
Depositing User:	Ю. Д. Жданова
Date Deposited:	04 Apr 2024 07:26
Last Modified:	10 Apr 2024 10:35
URI:	https://elibrary.kubg.edu.ua/id/eprint/48539

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