Intelligence Theories and Methods

933 Mapping of Multilevel Science-Technology Classification Systems in All Fields Hot! Xu Shuo, Zhang Yuefu, An Xin DOI: 10.3772/j.issn.1000-0135.2025.08.001 Innovation is deeply rooted in the creation, flow, and application of knowledge. However, various scientific and technological resource databases differ in their compilation principles and system architectures; this poses challenges in promoting the flow of scientific and technological knowledge and advancing scientific and technological innovation. This study proposes a hierarchical mapping paradigm for science-technology classification systems, aiming to establish multilevel mapping between scientific and technological taxonomies in all fields, thereby promoting unobstructed knowledge flow. Building on this, the study systematically analyzes the effect of scientific non-patent citations from different positions on mapping outcomes. The results reveal extensive knowledge flows between the scientific and technological domains at all levels, with diverse patterns of knowledge exchange in different fields. Scientific fields such as biology, chemistry, computer science, and medicine exhibit the most active knowledge diffusion that primarily converges into IPC sections, including Sections C (Chemistry; Metallurgy), A (Human Necessities), and G (Physics). Moreover, the analysis indicates that classification system mappings based on front-page citations display significant advantages in terms of mapping coverage, intensity, and accuracy of science-technology category mapping relationships, suggesting that citations from distinct positions reflect heterogeneity in purpose, functionality, and target audience. 2025 Vol. 44 (8): 933-949 [Abstract] ( 221 ) HTML (198 KB)  PDF (3115 KB)  ( 208 )

950 An Approach to Identifying Transformative Research by Integrating Citation Function and Triangular Citation Structure Hot! Zheng Zhejun, Ma Yaxue, Liang Zhentao, Bai Yun, Pei Lei DOI: 10.3772/j.issn.1000-0135.2025.08.002 Transformative research (TR) serves as a precursor to the emergence of new paradigms or disciplines in science and technology. Identifying TR is important for R&D management and technological forecasting. In response to the gaps in considering how citations of different functions impact the evaluation of focal papers, this study proposed a novel approach to identifying TR by integrating the citation function and triangular citation structure. By obtaining the triangular citation structure among the focal paper, its predecessor, and its successor based on different combinations of citation functions, we extracted the relationships of consolidation or disruption between the papers. An egocentric consolidation-disruption citation network (ECCD) was constructed for each focal paper. The ECCD network structure and text input were employed to build a heterogeneous graph attention neural network model, which was used to identify TR that possessed both high academic impact and peer-reviewed disruptive papers. An empirical analysis of the PubMed Central dataset Open Access subset revealed that the TR identification task achieved an optimal F1-score of 0.3926, which exceeded that of other baseline models. Further parameter analysis showed that disruptive citations interpreted by the citation function played a critical role in identifying high-impact and transformative research. 2025 Vol. 44 (8): 950-961 [Abstract] ( 194 ) HTML (155 KB)  PDF (2995 KB)  ( 255 )

962 Research on the Identification of Emerging Technologies Integrating Multidimensional Perspectives Hot! Li Guojun, Xie Fei, Tang Xinglong, Wang Bingqi, Xu Yang DOI: 10.3772/j.issn.1000-0135.2025.08.003 Emerging technologies are characterized by high degrees of innovativeness, uncertainty, and impact. They serve as the foundation of scientific innovation and a driving force for development. They are also critical elements of national competitiveness and security. Effectively identifying and monitoring these emerging technologies are significant challenges in science, technology management, and policymaking. Considering the complexity and diversity of emerging technologies, no unified or widely accepted definition has been identified. In this study, we review the definitions and characteristics of emerging technologies from three perspectives—scientometrics, complex networks, and evolutionary theory—along with the key indicators associated with each. Following this review, we propose a multidimensional framework for the selection of emerging technologies, integrating indicators from different perspectives into a comprehensive structure for identifying such technologies. Finally, using scientific papers from the OpenAlex dataset as the data source, we screen all computer science papers published between 2013 and 2022. By employing bibliometric clustering and citation analysis, we calculate and analyze multidimensional indicators to extract key terms and technologies. We validate and refine these results to produce a list of candidate emerging technologies, providing a reference for monitoring and predicting emerging technologies. 2025 Vol. 44 (8): 962-976 [Abstract] ( 194 ) HTML (189 KB)  PDF (1521 KB)  ( 272 )

977 Evaluation Significance of Patents Cited by Humanities and Social Sciences Papers from the Perspective of Philosophy of Technology Hot! Li Rui, Gou Yang, Zhuang Zhibo DOI: 10.3772/j.issn.1000-0135.2025.08.004 The international authoritative patent intelligence firm, CHI, incorporated the “citations” between patents and scientific papers into the patent measurement indicator system that has been widely used for over two decades. However, the phenomenon of patents being cited by humanities and social sciences papers has rarely been studied. This paper is based on two opposing theories within the philosophy of technology: the technological critique theory of the traditional pessimistic humanistic faction and the actor-network theory of the modern social construction faction and proposes two contrary hypotheses. The first hypothesis assumes that the attitude of the humanities and social sciences toward technological inventions is one of concern and critique, thus hypothesizing that the vitality of patents is negatively correlated with the frequency of their citation (critique) by humanities and social sciences papers. The second hypothesis assumes that the relationship between the humanities and technological inventions is one of dialogue, negotiation, and mutual construction, thus hypothesizing that the vitality of patents is positively correlated with the number of humanities disciplines citing them (dimensions of dialogue and negotiation) and with the betweenness centrality in the two-mode network (importance in social construction). Through an empirical study of global patents cited by A&HCI and SSCI journal papers, the first hypothesis is refuted, and the second hypothesis is validated, indicating that the current attitude of the humanities and social sciences toward technological inventions is not one of concern and critique but rather one of dialogue and negotiation. Furthermore, the richer the dimensions of negotiation and mutual construction, the stronger the vitality of the patents. Additionally, the more important the position of technological inventions in the social relational structure, the greater their vitality. The patent intelligence community is suggested to pay attention to the phenomenon of patents being cited in humanities and social sciences papers. By measuring the “disciplinary richness” of the citing side and analyzing the structural characteristics of the two-mode citation network, the more comprehensive evaluation and foresight of patent vitality can be provided. 2025 Vol. 44 (8): 977-986 [Abstract] ( 138 ) HTML (105 KB)  PDF (1702 KB)  ( 135 )

987 Do Knowledge Attributes from a Heritage and Innovation Perspective Contribute to the Technological Impact of Papers? Hot! Li Bing, Ding Kun, Sun Xiaoling, Larivière Vincent DOI: 10.3772/j.issn.1000-0135.2025.08.005 Citations of scientific papers on patented technologies manifest the technological impact of these papers. However, the types of scientific papers that are more likely to generate technological impact and the extent of that influence remain ambiguous. Unlike the uncertainties associated with external influencing factors, the inherent knowledge within scientific papers remains constant after being published. Consequently, this study adopted a perspective grounded in knowledge heritage and innovation. Publication data from the Web of Science database for papers published between 2000 and 2009 and patent data from the United States Patent and Trademark Office (USPTO) covering 2000 to 2020 were considered. Based on the source, knowledge characteristics were subdivided into interdisciplinary nature and content innovativeness. The aim was to explore whether knowledge characteristics influence the technological impact generated by scientific papers. After determining their influence on the technological impact of scientific papers, the study further analyzed their role in determining the degree of technological impact, including intensity, breadth, and speed. The research revealed that papers characterized by rich interdisciplinary diversity, low balance, distinctiveness, and high levels of innovative content are more likely to have a technological impact. Nonlinear relationships were observed between the interdisciplinary nature in different dimensions and intensity, breadth, and speed of the technological impact. Notably, papers with relatively low levels of content innovativeness tend to have greater power, wider scope, and rapid technological impact. Finally, in considering papers with varying levels of innovation, the effects of variety, balance, and disparity on the speed of technological influence were more pronounced, and the impact of Rao-Stirling on the intensity and breadth of technological influence was more distinct. 2025 Vol. 44 (8): 987-1002 [Abstract] ( 156 ) HTML (312 KB)  PDF (1973 KB)  ( 78 )

1003 Three-Dimensional Measurement of Scientific Collaboration Sustainability: Library and Information Science (LIS) and Physics & Astronomy (PHYS) as Examples Hot! Liu Xiaoting, Huang Ying, Zhang Hui, Li Ruinan, Zhang Lin DOI: 10.3772/j.issn.1000-0135.2025.08.006 A clear understanding of the sustainability of scientific collaboration can help researchers optimize resource allocation, effectively preserve academic resources, and enhance research performance. We initially established a rationale for analyzing scientific collaboration sustainability based on three dimensions of collaboration: persistence, stability, and adhesion. Subsequently, relevant measurement indices were developed . A case study was conducted involving researchers in Library and Information Sciences (LIS) and Physics & Astronomy (PHYS), to examine the characteristics of collaborative sustainability and evaluate its impact on academic performance. Our findings revealed that despite the specific differences in the data distribution characteristics of the two fields, the overall trends were generally similar. Collaboration pairs with higher levels of collaboration persistence and adhesion tended to have a greater average number of publications and a stable collaboration environment. Interestingly, the collaboration pairs that exhibited the highest levels of persistence, stability, and adhesion did not necessarily achieve the highest average citation frequency nor were they among the highest percentage of highly cited articles. Collaboration pairs with moderate to high levels of these dimensions demonstrated the best overall performance. 2025 Vol. 44 (8): 1003-1016 [Abstract] ( 126 ) HTML (139 KB)  PDF (3727 KB)  ( 90 )

1017 Research on the Identification of Heterogeneous Network Policy Collaboration Groups in Complex Situations Hot! Guo Hua, Jiang Ying, Hou Baiyi, Pang Ruoxin, Liu Liwen DOI: 10.3772/j.issn.1000-0135.2025.08.007 Diverse actors construct collaborative networks to formulate and implement policies in complex policy situations. Policy collaboration groups are small, cohesive subsets of actors who engage in collaborative actions involving specific policy goals or tools. Identifying and understanding these groups is crucial for clarifying collaborative structures and interpreting collaborative patterns. However, existing research often separates policy networks from policy processes, making it difficult to perform a holistic analysis of policy information. This situation leads to poor handling of conflicts and ambiguities within groups. This paper presents a systematic perspective and proposes a method for identifying heterogeneous network policy collaboration groups based on a “network+process” two-dimensional framework aimed at analyzing diverse actors, policy goals, tools, and collaborative relationships in complex policy situations. A case study verifies the feasibility of the proposed method, which characterizes the heterogeneity of groups and their boundaries, composition, and connotations and provides new ideas and empirical support for a deeper understanding of policy collaboration system features and models. 2025 Vol. 44 (8): 1017-1030 [Abstract] ( 152 ) HTML (161 KB)  PDF (3884 KB)  ( 81 )

1031 Construction of a Digital Health Literacy Framework and Cultivation Path for Older Adults in the Context of Smart Elderly Care Hot! Cao Gaohui, Dong Huanqing, Chen Yifan DOI: 10.3772/j.issn.1000-0135.2025.08.008 A smart pension model provides comprehensive health management and safety monitoring services for the elderly using information technology. As the main service object of this model, the level of digital health literacy of the elderly affects the effectiveness of smart elderly care services, and the importance of digital health literacy among the elderly is becoming increasingly prominent. The study first used the competency model as a foundational framework and, by integrating the Global Digital Literacy Framework, European Digital Competence Framework, Digital Intelligence Framework, Eshet-Alkalai Digital Literacy Conceptual Framework, and Nutbeam Health Literacy Model, constructed a digital health literacy framework for older adults from four dimensions: knowledge, skills, attitudes, and ethics. Then, it explained the components of the framework at the micro level. Finally, based on this, it proposed a cultivation path for the digital health literacy of older adults focusing on four aspects: knowledge dissemination, skills training, attitude development, and ethics education. In the context of smart aging, clarifying the framework of elderly digital health literacy, its elements, and the pathways for cultivating elderly digital health literacy is of great significance for improving the digital health literacy of the elderly, promoting digital health literacy education for the elderly, and helping them better integrate into the digital health management system. 2025 Vol. 44 (8): 1031-1044 [Abstract] ( 113 ) HTML (121 KB)  PDF (1976 KB)  ( 1705 )

Intelligence Users and Behavior

1045 Empirical Study and Construction of a User Privacy Paradox Behavior Portrait Model in Human-AI Interaction Scenarios Hot! Mao Taitian, Tang Gan, Zhou Zhizhen DOI: 10.3772/j.issn.1000-0135.2025.08.009 To explore the causal factors and behavioral outcomes of users' privacy paradox behavior in human-artificial intelligence (AI) interaction contexts, this study aimed to develop a model for user privacy paradox behavior and conduct persona analysis. This research provides theoretical support for optimizing user experience and formulating privacy protection policies. A combination of online surveys and semi-structured interviews was used along with grounded theory, to extract the key factors. Based on the stressor-strain-outcome (SSO) and information ecology theories, this study constructed a persona model of privacy paradox behavior in human-AI interaction contexts. Through a K-means clustering analysis of the survey data, four distinct persona types were identified: proactive explorers, cautious defenders, rational balancers, and passive avoiders. These findings offer comprehensive insight into the privacy paradox behavior types of users on AI-generated content platforms. 2025 Vol. 44 (8): 1045-1057 [Abstract] ( 134 ) HTML (143 KB)  PDF (2010 KB)  ( 1003 )

Intelligence Reviews and Comments

1058 Review of Large Language Model Evaluation Studies: Current Status, Applications, Challenges, and Trends Hot! Zhao Xue, Zhang Hai, Wang Dongbo DOI: 10.3772/j.issn.1000-0135.2025.08.010 Evaluating large language models (LLMs) is integral to scientific evaluation frameworks. This study delves into the core concepts and implications of LLM evaluations and examines the current status, applications, limitations, and future directions to advance research and applications in this field. We track the latest developments in LLM evaluation studies and analyze the status quo, applications, constraints, and evolving trends of LLM evaluations. The findings reveal hundreds of benchmarks for the capacities of understanding and generation, knowledge acquisition, ethical safety, and multimodal processing. Existing studies predominantly focus on assessing the general capabilities of LLMs while gradually expanding into specialized domains. However, the field faces challenges, such as the need for a systematic evaluation framework, insufficient diversity in datasets, and reliance on singular evaluation techniques. Establishing a standardized scientific evaluation system, conducting multimodal evaluation research, extending evaluations to specific areas, and integrating user studies have been identified as the frontiers of LLM evaluations. 2025 Vol. 44 (8): 1058-1074 [Abstract] ( 217 ) HTML (238 KB)  PDF (939 KB)  ( 453 )