ANALYSIS AND MODELLING THE PREFERENCES OF SOCIAL NETWORKS USERS
Journal Title: Сучасний стан наукових досліджень та технологій в промисловості - Year 2018, Vol 3, Issue 1
Abstract
The subject matter of the research is the models and technologies of analyzing the processes of developing the loyalty and preferences of social networks users. The goal of the research is to increase the efficiency of marketing analysis of clients’ preferences and promoting products and services. The following tasks are solved in the article: the analysis of the methods and technologies of simulation modelling; the survey of available simulation packages; designing a datalogical context chart; developing the agent-based model of the impact of social networks on preferences; developing a database for data storage; a graphical analysis of preferences. The following research methods are used – simulation modelling methods, Laravel and YouTube Data and Analytics API methods. The following results were obtained: the model that explains how advertising affects the development of clients’ preferences, as well as the impact of clients’ communication on loyalty, the information system for the graphical analysis of Wow–How Studio of YouTube channel The model that reveals the impact of advertising and clients’ communication was developed. The suggested model proves the fact that the communication of social networks users greatly increases a number of actual clients as well as the level of loyalty. Using such technologies as Laravel and YouTube Data API, the designed application enables clear and timely monitoring and analyzing Wow-How Studio channel, which is very important to be always aware of the preferences of potential clients and to know what can be interesting for them and how to meet their expectations. The results can be implemented in enterprises of various spheres that offer their products and services. Any company is interested in obtaining the maximum profit and integration into social networks is free advertising and as a result attracts additional profit.
Authors and Affiliations
Bohdan Haidai, Roman Artiukh, Olga Malyeyeva
Keywords
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- EP ID EP472202
- DOI 10.30837/2522-9818.2018.3.005
- Views 58
- Downloads 0
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