| Issue |
E3S Web Conf.
Volume 614, 2025
International Conference on Agritech and Water Management (ICAW 2024)
|
|
|---|---|---|
| Article Number | 05006 | |
| Number of page(s) | 8 | |
| Section | Application of IT Technologies in Ecology and Natural Resource Management | |
| DOI | https://doi.org/10.1051/e3sconf/202561405006 | |
| Published online | 07 February 2025 | |
Green-oriented automation: AI-driven engineering control technologies for resource-efficient solutions
1 University of friendship of people’s academician A. Kuatbekov, Shymkent, Kazakhstan
2 M. Auezov South Kazakhstan University, Shymkent, Kazakhstan
3 Khoja Akhmet Yassawi International Kazakh-Turkish University, Turkistan, Kazakhstan
* Corresponding author: toktar.aigerim@list.ru
This article is not only about the speed of digital life in human history, also about its second aspect, that is, the existence of Internet users who use online content for the purpose of insulting or degrading, as well as collecting comments written on social networks with obscene words. It is said that simple and automated actions can be implemented using machine learning. Today, the prevalence of negative comments on online content further exacerbates the problem. Cyberbullying is known to be one of the threats posed by online content, which, in turn, puts online users in an emotional state and causes certain psychological damage. We are collecting a database of obscene comments posted on social networks and used by the media in Kazakhstan. Analyzing complaints received from many social networks, we noticed that the number of publications with offensive, that is, derogatory comments in online content is increasing every day. The results of our research using machine learning methods will help not only to study the roots of abusive language posted on social networks, but also to distinguish the types of offensive comments and obtain automated data sets.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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