Sentiment analysis plays an important role in understanding employee feedback and improving workplace culture. By leveraging NLP techniques to analyze this feedback accurately, organizations can pinpoint specific areas that need improvement, address employee concerns, and foster a positive work environment. These NLP-driven deep learning models offer valuable tools for E-Commerce HR and sales departments, enabling monitoring employee and users’ sentiment trends over time and assisting in implementing targeted interventions. Focusing on the e-commerce industry, this work utilizes NLP-driven deep learning methodologies to analyze employee and user feedback, aiming to identify sentiments. The proposed NLP-driven, deep learning-based framework is designed to classify user feedback into positive, negative, or neutral sentiments. The key steps in this framework include data collection, NLP-enhanced feature extraction using BERT-BiGRU, and final classification using a Graph Neural Network-based finite-state automata. The effectiveness of this NLP-centric approach was tested on diverse datasets of customer feedback from the e-commerce industry. The results demonstrate the framework’s efficacy, achieving an impressive 93.35% accuracy rate, surpassing existing benchmark methods. The research significantly benefits e-commerce by refining product portfolios and enhancing workplace culture.

At the time when great emphasis is being placed on environmental protection as well as on the introduction of environmental safeguards, we are faced with an undesirable phenomenon—environmental crime. Environmental crime represents one of the fastest growing security issues. It is a criminal activity, and like other crimes, it has serious consequences that are costly to eliminate. This article uses systematic analysis and, through scientific methods, points out the growth of environmental crime in Slovakia. At the same time, it introduces possible prevention tools. Our aim is to specify the term ‘environmental crime’, present the legal aspects of environmental crimes by focusing on Slovak legal regulation, extend the topic to bentonite mining and processing companies, map environmental crime in the EU Member States, and clarify the nature of environmental crime as well as the legal basis for the protection of the environment in Slovakia. The findings and conclusions have the potential to introduce a new approach to mapping the topic of environmental crimes, provide recommendations for the prevention of this type of crime, and open a discussion on the actual global problem. It is evident that the effective fight with environmental crime requires a complex and multidisciplinary approach at all levels. This includes, in particular, the use of relevant national policies and instruments, as well as those of the European Union and other international organizations.

The method of the analysis of different texts styles is developed in the paper. Integer numerical sequences are used as models. The elements of the sequence are the number of letters in the words of the text. The algorithm for calculating the exact value of the fractal dimension is developed. It provides the determination of the exact value of the Hurst index. The value of the power dependence constant is calculated. The obtained indicators in the aspect of fractality completely describe the objects of research.

Purpose: The study aims to explore the dynamics shaping online education processes in the Visegrad countries (Poland, Czech Republic, Slovakia, and Hungary) during the transition to remote learning. Design/methodology/approach: A qualitative study was conducted among 40 university students and 40 academic teachers from the four countries. The data analysis focused on identifying recurring patterns and challenges in online teaching and learning experiences. Findings: The research revealed two negative cycles influencing online education. The first, called the cycle of declining engagement, shows how decreasing student engagement led to lower lecturer involvement, which in turn further reduced students’ motivation. The second, the hide-and-seek cycle, indicates that the more control tools were implemented to monitor students, the more strategies emerged to bypass the rules. The main challenges identified by participants included monotony, lack of social interaction, and lecturers’ psychological exhaustion caused by the absence of live contact with students. Research limitations/implications: The study was based on a relatively small qualitative sample, which limits the generalizability of results. However, it provides valuable insights into mechanisms that may be present in broader contexts of remote education. Originality/value: This research contributes to understanding the relational and motivational dynamics of online education by identifying feedback loops that undermine engagement and trust between students and lecturers.

The purpose of the article In recent years, digitalization and AI have created an ideal space for innovation in education. Modern education has to reflect the needs and interests of the generation we are currently educating at Universities – Generation Z, or Gen Z. Methodology/methods This paper uses basic scientific methods such as analysis, synthesis, comparison, observation, induction and deduction, questionnaire surveys, and descriptive statistics to present the results of research, providing a database of innovative solutions aimed at enhancing the quality of the educational process and graduate success. It identifies the current perceptions of the younger generation regarding the education system, highlights current innovative methods and techniques used in higher education, and emphasizes the advantages of a process-oriented and systematic approach to continuous improvement the quality of educational processes. The scientific aim of this paper is to analyse the current challenges for education, supported by the phenomenon of ""digitalization and AI"" to map the environment in which educational institutions operate, where students and educators with their requirements, demands, and expectations are an inseparable part, and to present examples of good practices that eliminate basic mistakes and shortcomings in the modernization and innovation of educational processes, especially from Generation Z education perspective. Findings The results provide students current perspective on some areas of education, the use of AI and its impact on innovative possibilities in education. Conclusions (limits, consequences, etc.) The results primarily include the identification of requirements for education in the field of management, a summary of procedures and tools used in education, formulated trends and modern innovative educational practices suitable for new Generation Z.