Under the background of the development of the network information age, the current Internet industry has obtained more development opportunities, but it has also brought corresponding challenges in the process of wide application. In the development and construction of modernization, society pays more attention to the supervision and determination of the characteristics of online public opinion. From the perspective of the current characteristics of network public opinion, because social information is more extensive and involves many fields, network public opinion has a high degree of complexity and diffusion. Therefore, it is necessary to strengthen the analysis and application of relevant data mining systems in order to achieve efficient management of network public opinion. The key to the disadvantage of the traditional excavation of public opinion communication characteristics lies in the lag of the excavation process, and it is difficult to deal with malignant public opinion in a timely and effective manner. Therefore, in order to truly solve the lagging problem of public opinion data dissemination feature mining technology, it is necessary to strengthen the application of artificial intelligence technology in it.

This study aims to investigate the difficulties local governments face as a result of the province directly managing county system reform. It reveals the various challenges faced by local governments under the provincial directly managed county reform through a thorough analysis of the history, rationale, and implementation of the reform along with pertinent literature reviews and case studies. It is discovered that the county reform, which is directly governed by the province, has not only significantly altered the functions and organizational structure of local governments, but it has also made their resource allocation, financial strain, and brain drain problems worse. To help local governments deal with the difficulties in the province-directly governed county reform, related remedies, and solutions are finally proposed to handle these issues.

Background: Bitcoin mining, an energy-intensive process, requires significant amounts of electricity, which results in a particularly high carbon footprint from mining operations. In the Republic of Kazakhstan, where a substantial portion of electricity is generated from coal-fired power plants, the carbon footprint of mining operations is particularly high. This article examines the scale of energy consumption by mining farms, assesses their share in the country’s total electricity consumption, and analyzes the carbon footprint associated with bitcoin mining. A comparative analysis with other sectors of the economy, including transportation and industry is provided, along with possible measures to reduce the environmental impact of mining operations. Materials and methods: To assess the impact of bitcoin mining on the carbon footprint in Kazakhstan, electricity consumption from 2016 to 2023, provided by the Bureau of National Statistics of the Republic of Kazakhstan, was used. Data on electricity production from various types of power plants was also analyzed. The Life Cycle Assessment (LCA) methodology was used to analyze the environmental performance of energy systems. CO₂ emissions were estimated based on emission factors for various energy sources. Results: The total electricity consumption in Kazakhstan increased from 74,502 GWh in 2016 to 115,067.6 GWh in 2023. The industrial sector’s electricity consumption remained relatively stable over this period. The consumption by mining farms amounted to 10,346 GWh in 2021. A comparative analysis of CO₂ emissions showed that bitcoin mining has a higher carbon footprint compared to electricity generation from renewable sources, as well as oil refining and car manufacturing. Conclusions: Bitcoin mining has a significant negative impact on the environment of the Republic of Kazakhstan due to high electricity consumption and resulting carbon dioxide emissions. Measures are needed to transition to sustainable energy sources and improve energy efficiency to reduce the environmental footprint of cryptocurrency mining activities.

Metaverse technology has various uses in communication, education, entertainment, and other aspects of life. Consequently, it necessitates using some interactive mobile applications to enter the virtual world and gain real-time, face-to-face experiences, particularly among students. This research focused on the factors accelerating metaverse technology acceptance particularly, Metaverse Experience Browser application acceptance among the students under the factors proposed by the unified theory of acceptance and use of technology (UTAUT) model. Notably, lack of studies in metaverse browsers and their prevalence during the post pandemic era, indicates a strong literature gap. The researchers gathered data from n = 384 higher education students from the two cities in the United Arab Emirates and applied Structural Equation modelling (SEM) for data analysis. Results revealed that Performance Expectancy (p < 0.003) and Social Influence (p = 0.000) were significant factors affecting the Behavioral Intention of the students to consider Metaverse Experience Browser as an interactive mobile application. On the other hand, behavioural Intention significantly affects (p = 0.000) Effort Expectancy, which shows how fewer efforts and greater accessibility are associated with one’s behavioural Intention. Besides, the effect of Behavioral Intention (p = 0.000) on Metaverse Experience Browser acceptance also remained validated. Finally, Effort Expectancy (p = 0.000) also indicated its significant effect on the Metaverse Experience Browser. These results indicated that the factors proposed by UTAUT have greater applicability on the Metaverse Experience Browser as they showed their relevance to its acceptance. The present study concludes that the acceptance of Metaverse Experience Browser as an interactive mobile application is a level ahead in improving students’ experiences. Thus, the Metaverse Experience Browser is considered a modified way of creating, sharing, participating, and enjoying the virtual world, indicating its greater usage among students for different purposes, including education and learning.

The study examines the economic and social impacts of a Southeast Asian multinational company operating in the northwestern region of Hungary, with a particular focus on the local labor market and community responses. The research aims to explore the company’s location choice motivations, its integration process into the local economy, and its cooperation with the local government and communities. The research provides a comprehensive picture of the company’s impacts by employing qualitative and quantitative methodologies—including management interviews and household surveys. The findings indicate that the company has significantly increased employment, enhanced infrastructure, and promoted cultural diversity. However, challenges related to cultural integration persist. The study offers valuable guidance for policymakers and businesses on leveraging the economic benefits of foreign investments and fostering cultural cooperation. Future research could delve deeper into the long-term socio-economic impacts.

This research seeks to identify the value of a few common factors determining the speed of economic growth in Baltic states and analyzes their impact in detail on Latvia’s lagging. Latvia’s economic starting point after regaining independence because of the collapse of the Soviet Union was at least comparable to its neighbors. Still, after the implementation of liberal reforms towards a free market’ economy and 20 years of operation as an EU full member, Latvia is lagging in growth, prosperity, and innovation. Within the analysis, this scientific paper pays special attention to the three less discussed factors, namely, the impact of post-Soviet mind-set effects as a part of local innovation culture, lasting since regaining independence in 1991; the importance of the availability of talent pull, its density, diversity, and accessibility; and readiness and capability to capture external knowledge and technology adoption. The overall approach is the systemic assessment of the national innovation system and/or innovation ecosystem, trying to understand the differences between these two models. Research is performed by analysis of the performance of the local innovation ecosystem in connection with export- and Foreign Direct Investment (FDI) policies. The authors present a novel method for visually representing economic growth and its application in analyzing process development within transitional economic nations. The study uses an analytical and synthetical literature review. It offers a new GDP data visualization method useful for monitoring economic development and forecasting potential economic crises—the outcomes from aggregative literature analysis in a consolidated concept are provided for required talent policy proposals. The post-Soviet mindset is seen as a heritage and devious underdog that has left incredibly diverse consequences on today’s society, power structures, economic growth potential, and the emergence of healthy, well-managed, and sustainable innovation ecosystems. The post-Soviet mindset is a seemingly hidden and, at the same time, an intriguing factor that has a significant impact on the desire to make and implement the right decisions related to innovation, education, and other policies promoting business development. The key outcome of the article is that sociocultural aspects and differences in innovation culture led to a slow-down of Latvia’s economic growth compared to Estonia’s and Lithuania’s slightly more successful economic reforms.