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.

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.

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.