This paper uses quantitative research methods to explore the differences in the impact of virtual influencers on different consumer groups in the context of technological integration and innovation. The study uses DBSCAN (Density-Based Spatial Clustering of Applications with Noise) clustering technology to segment consumers and combines social media behavior analysis with purchase records to collect data to identify differences in consumer behavior under the influence of virtual influencers. Consumers’ emotional resonance and brand awareness information about virtual influencers are extracted through sentiment analysis technology. The study finds that there are significant differences in the influence of virtual influencers on different consumer groups, especially in high-potential purchase groups, where the influence of virtual influencers is strong but short-lived. This paper further explores the deep integration of virtual influencer technology with new generation information technologies such as 5G and artificial intelligence, and emphasizes the importance of such technological integration in enhancing the endogenous and empowering capabilities of virtual influencers. The research results show that technological integration and innovation can not only promote the development of virtual influencers, but also provide new technical support for infrastructure construction, especially in the fields of smart cities and industrial production. This paper provides a new theoretical perspective for the market application of virtual influencers and provides practical support for the application of virtual technology in infrastructure construction.

This study empirically examines the complex relationship between materialism and economic motivation, proposing an inverted U-shaped relationship. The research analyzes three dimensions of materialism: happiness pursuit, social recognition, and uniqueness, and their impact on economic motivation. The findings suggest that materialism, when balanced, positively influences economic motivation without causing adverse effects. This relationship remains consistent across demographic characteristics and life satisfaction levels, challenging the traditional negative view of materialism. The implications of these findings extend to marketing strategies, policy design, and infrastructure development, offering actionable insights for real-world contexts. This research underscores the importance of balancing materialistic values to foster sustainable economic growth and well-being.

Named Entity Recognition (NER), a core task in Information Extraction (IE) alongside Relation Extraction (RE), identifies and extracts entities like place and person names in various domains. NER has improved business processes in both public and private sectors but remains underutilized in government institutions, especially in developing countries like Indonesia. This study examines which government fields have utilized NER over the past five years, evaluates system performance, identifies common methods, highlights countries with significant adoption, and outlines current challenges. Over 64 international studies from 15 countries were selected using PRISMA 2020 guidelines. The findings are synthesized into a preliminary ontology design for Government NER.

Yunnan is rich in cultural heritage, with its primitive pottery techniques coexisting with modern pottery techniques, and is known as the “Museum of Ceramic History”. Due to regional and socio-economic development factors, some folk pottery and craftsmen have faded out of sight or only circulated in a few small areas and specific environments. The study analyzes and summarizes the characteristics of Yunnan folk pottery and industry and evaluates the Yunnan folk pottery value based on the conditional valuation method. The study takes the folk pottery of the Bai nationality in Dali, Yunnan as an example and obtains the evaluation results of the purchasing motivation value of the pottery through a questionnaire survey. 45.26% of people pay for their existence value, 26.03% pay for their choice value, and 28.71% pay for their legacy value. Based on the evaluation results, the study proposes targeted activation paths for Yunnan folk pottery, including innovative development combined with new technologies, highlighting the functional characteristics of pottery, and brand building. This study will help Yunnan folk pottery find more suitable ways of protection and inheritance in the rapid development of materials and technology. This study can help inheritors gain the possibility of sustainable development and provide reference value for the activation path of other traditional folk.

The construction of researcher profiles is crucial for modern research management and talent assessment. Given the decentralized nature of researcher information and evaluation challenges, we propose a profile system for Chinese researchers based on unsupervised machine learning and algorithms. This system builds comprehensive profiles based on researchers’ basic and behavior information dimensions. It employs Selenium and Web Crawler for real-time data retrieval from academic platforms, utilizes TF-IDF and BERT for expertise recognition, DTM for academic dynamics, and K-means clustering for profiling. The experimental results demonstrate that these methods are capable of more accurately mining the academic expertise of researchers and performing domain clustering scoring, thereby providing a scientific basis for the selection and academic evaluation of research talents. This interactive analysis system aims to provide an intuitive platform for profile construction and analysis.

Over the past decade, the integration of technology, particularly gamification, has initiated a substantial transformation within the field of education. However, educators frequently confront the challenge of identifying suitable competitive game-based learning platforms amidst the growing emphasis on cultivating creativity within the classroom and effectively integrating technology into pedagogical practices. The current study examines students and faculty continuous intention to use gamification in higher education. The data was collected through an online survey with a sample size of 763 Pakistani respondents from various universities around Pakistan. The structural equation modeling was used to analyze the data and to investigate how continuous intention to use gamification is influenced by, extended TAM model with inclusion of variables such as task technology fit, social influence, social recognition and hedonic motivation. The results have shown that task technology has no significant influence on perceived usefulness (PU) where as it has a significant influence on perceived ease of use (PEOU). Social influence (SI) indicates no significant influence on perceived ease of use. Social recognition (SR) indicates positive influence on perceived usefulness, perceived ease of use, and continuous intention. The dimensional analysis indicated that perceived ease of use has insignificant influence on perceived usefulness. Both PEOU and PU exhibit positive influence on attitude. Hedonic motivation (HM) and attitude were observed to have a positive influence on continuous intention (CI). Moreover, gamification is found to efficiently and effectively achieve meaningful goals by tapping intrinsic motivation of the users through engaging them in playful experiences.