Analysis of technologies for personalized content recommendations on the internet

Authors

  • Oleksii Lopakov Odessа Polytechnic National University
  • Lada V. Prokopovich Odessа Polytechnic National University
  • D. Solodkyi Odessа Polytechnic National University

DOI:

https://doi.org/10.15276/opu.1.65.2022.10

Keywords:

social networks, advertising, news “feeds”, content ranking algorithms, “information corridors”

Abstract

The introduction of new technologies in the social information sector of the Internet is primarily due to increasing competition for the attention of users. In order to keep a person’s attention on your social network, you only need constantly to offer interesting, diverse content, and it should be different for different users. To solve these practical problems, technologies for personalized content recommendations are being developed. The relevance of the topic of this article is due to the widespread use on the Internet of personalized content recommendations and the emergence of publications (analytical materials, statistics), which address the shortcomings of these technologies. The purpose of the study is to analyze modern technologies of personalized content recommendations with the identification of positive and negative consequences of their practical application. The paper analyzes the algorithms of content ranking, which are used by various social networks, video hosting and other media resources. Theoretical substantiation of risks connected with creation of “information corridors” is given. The study found that these technologies could facilitate the process of users to search and consume information through recommendations only interesting content; personalization of advertising, facilitation of targeting; reducing the amount of harmful information or traumatic content. At the same time, these technologies lead to negative consequences: problems of censorship; information restrictions, or “information corridors”; influence on concentration and way of thinking. The presence of these problems does not allow calling the current technical achievements in the field under study, the ultimate. However, this applies to any technology that requires not only recognition of their benefits, but also careful analysis of shortcomings in order to timely correct them and establish the principles of responsible use of these technologies.

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References

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Published

2022-03-26

How to Cite

[1]
Lopakov, O., Prokopovich, L.V. and Solodkyi, D. 2022. Analysis of technologies for personalized content recommendations on the internet. Proceedings of Odessa Polytechnic University. 1(65) (Mar. 2022), 83–89. DOI:https://doi.org/10.15276/opu.1.65.2022.10.

Issue

Section

Informacion technology. Automation

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