Following scholars in Scientometrics as examples, we develop five author relationship networks, namely, co-authorship, author co-citation (AC), author bibliographic coupling (ABC), author direct citation (ADC), and author keyword coupling (AKC). The time frame of data sets is divided into two periods: before 2011 (i.e., T1) and after 2011 (i.e., T2). Through quadratic assignment procedure analysis, we found that some authors have ABC or AC relationships (i.e., potential communication relationship, PCR) but do not have actual collaborations or direct citations (i.e., actual communication relationship, ACR) among them. In addition, we noticed that PCR and AKC are highly correlated and that the old PCR and the new ACR are correlated and consistent. Such facts indicate that PCR tends to produce academic exchanges based on similar themes, and ABC bears more advantages in predicting potential relations. Based on tripartite citation analysis, including AC, ABC, and ADC, we also present an author-relation mining process. Such process can be used to detect deep and potential author relationships. We analyze the prediction capacity by comparing between the T1 and T2 periods, which demonstrate that relation mining can be complementary in identifying authors based on similar themes and discovering more potential collaborations and academic communities.

The Belt and Road Initiative, proposed by the Chinese government in 2013, has exerted great influence, not only on geopolitics and the economy but also on scientific research. This paper investigates the relationship between scientific collaboration and knowledge production of the countries participating in the Belt and Road Initiative project. To this end, we used 314,678 co-authored papers and 6,226,577 paper publications in these countries from 2009 to 2018 to measure scientific collaboration and knowledge production, respectively. Additionally, we selected the country’s economic level, the number of specialized disciplines, and political stability as influencing indicators. Methodologically, we established a dynamic panel model and used the generalised method of moments to empirically analyze the relationship between the two and the influencing factors. The results reveal that the scientific collaboration and knowledge production of the countries along the Belt and Road Initiative are mutually reinforcing and show accumulative effects. The number of specialized disciplines and political stability are major influencing factors for scientific collaboration and knowledge production. Knowledge production can facilitate scientific collaboration by increasing number of specialized disciplines, economic development and political stability. Scientific collaboration can weaken the promotion of knowledge production in a similar way, exclusive of economic development.

This study examines the regional co-funding network as a novel framework for advancing high-quality fundamental research amid systemic reforms in science funding. Based on provincial joint funding data from Mainland China retrieved via the WoS-SCIE and SSCI databases (2013–2022), an interprovincial co-funding network was constructed. Social network analysis, kernel density estimation, and fixed-effects regression analysis were employed to explore the evolution of regional location advantages and their impact on technological innovation. The findings reveal that the co-funding network has become increasingly balanced over time, significantly enhancing the location-based innovation advantages of individual provinces and strengthening the network’s overall capacity to foster innovation. This improved equilibrium has positively influenced regional scientific output, demonstrating that a province’s position within the co-funding network—particularly its individual location advantage—plays a pivotal role in advancing technological progress. However, persistent disparities in regional collaboration and development remain, underscoring the need for more coordinated strategies to address uneven growth dynamics. By introducing the co-funding network as an analytical lens, this study uncovers the hidden channels of resource synergy and their influence on regional innovation. The results provide actionable insights for optimizing co-funding mechanisms and enhancing interprovincial collaboration to maximize innovation potential in China.

1. International trade is an essential component of the modern global economic system and serves as a core driving force in the promotion of national economic development. From the perspective of t...