Intelligence Theories and Methods

1003 Interdisciplinarity, Temporal Diversity, and Scientific Impact: Perspective on References Hot! Yang Alex J., Wang Zuorong, Deng Sanhong, Wang Hao, Zhang Xuezhou DOI: 10.3772/j.issn.1000-0135.2024.09.001 Building on the concept of interdisciplinarity, this study proposes a measurement framework for temporal diversity, quantifying it into four dimensions: temporal richness, temporal imbalance, temporal disparity, and temporal depth. The study meticulously analyzes the temporal trends and distribution characteristics of interdisciplinarity and temporal diversity, as well as the career evolution patterns of high-level scientists, using 38,879,575 scientific papers from the Microsoft Academic Graph database spanning from 1950 to 2020. The relationship between interdisciplinarity, temporal diversity, and scientific impact is further explored. The findings reveal that: (1) The interdisciplinary and temporal diversity of papers exhibits a consistent growth trend that differs depending on the field. (2) Both interdisciplinarity and temporal diversity indicators show heterogeneous distribution characteristics, such as scale-free distribution, and a weak correlation exists between them. (3) In the careers of high-level scientists, both interdisciplinarity and temporal diversity show significant growth trends, largely attributable to an increase in the number of their referenced papers. (4) Interdisciplinarity and temporal diversity have opposite effects on scientific impact with interdisciplinarity significantly promoting scientific impact and temporal diversity significantly inhibiting it, suggesting that a combination of strong interdisciplinarity and weak temporal diversity has the highest probability of becoming a disruptive hotspot paper. The temporal diversity measurement framework proposed in this study enriches the theories of knowledge integration and interdisciplinarity, providing insights into science and technology policy and academic evaluation. 2024 Vol. 43 (9): 1003-1014 [Abstract] ( 39 ) HTML (168 KB)  PDF (4167 KB)  ( 85 )

1015 Research on Influencing Factors of Value Co-Creation Behavior of Metaverse Platform Users Based on Mixed Research Methods Hot! Wang Xiwei, Bi Yingying, Li Mali DOI: 10.3772/j.issn.1000-0135.2024.09.002 In recent years, the metaverse has become an active topic in academia and industry. Analyzing the factors influencing the value co-creation behavior of users on metaverse platforms can be useful to understand this behavior, identify the bottlenecks and solutions in the development of metaverse platforms, and promote the organic integration of metaverse technology in various industries. Using a mixed research method, the representative metaverse platform NetEase Yaotai in China was selected as the experimental object. In the qualitative research stage, semi-structured interviews were conducted with 24 NetEase Yaotai users, and the interview content was analyzed through qualitative coding to explore the preliminary factors influencing the user value co-creation behavior on the metaverse platform. In the quantitative research stage, a model of the factors influencing the value co-creation behavior of metaverse platform users was constructed by combining relevant literature on value co-creation theory and social support theory. A questionnaire survey was used to collect data, and the structural equation method was applied to empirically verify and analyze the constructed model. The results of the empirical research show that human-human interaction and human-computer interaction have a significant positive influence on social support, which has a significant positive impact on the willingness to co-create value among users of the metaverse platform. The degrees of freedom, avatar, and immersion quality of the metaverse platform capabilities have a significant positive influence on the willingness of metaverse platform users to co-create, whereas value, privacy, and security risks have a significant negative influence. The willingness of users to co-create value on the metaverse platform has a significant positive impact on users' value co-creation behavior. 2024 Vol. 43 (9): 1015-1031 [Abstract] ( 23 ) HTML (207 KB)  PDF (1721 KB)  ( 51 )

1032 The Process Model and Mechanism of Value Co-Creation for Open Data Competitions in Digital Humanities Hot! Zhang Yan, Zhao Yuxiang, Liu Wei, Zhu Qinghua DOI: 10.3772/j.issn.1000-0135.2024.09.003 Open and shared data play crucial roles in building data ecosystems. Open data competition in digital humanities can facilitate the transformation of cultural digitization achievements and promote widespread accessibility. An exploratory case study approach from the perspective of service ecosystems was adopted for this study, and data were obtained from four editions of the Shanghai Library Open Data Competition to analyze the process and underlying mechanisms of value co-creation among competition actors. This research identified the emerging values—historical, economic, experiential, social, cultural, and societal—generated from open data competitions in digital humanities. The co-creation process model encompasses value consensus, co-generation, co-integration, and co-dissemination. An iterative transformation between implicit value propositions and explicit product values forms a continuous and dynamic spiral of value co-creation. The value output of the competition demonstrates a trend of sustained growth as the ecosystem continued to expand. This study supplements phenomenological research on value co-creation processes and mechanisms from the perspective of service ecosystems and provides recommendations for open innovation information practices in the digital humanities. 2024 Vol. 43 (9): 1032-1045 [Abstract] ( 19 ) HTML (130 KB)  PDF (3789 KB)  ( 34 )

1046 Online-Media Situation Awareness: Development of Theoretical Framework Based on Systematic Literature Review Hot! Huang Meiyin, Wang Fang, Liu Qingmin DOI: 10.3772/j.issn.1000-0135.2024.09.004 The situational awareness of online media has received attention from both industry and academia. However, the related studies are unorganized. By systematically reviewing the relevant literature, this study provides a systematic understanding of online-media situation awareness to promote communication between different fields. The PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) method is employed to obtain and organize SSCI (Social Sciences Citation Index)/SCI (Science Citation Index)/CSSCI (Chinese Social Sciences Citation Index) literature. After performing content coding and analysis under the three-level framework of “perception, comprehension, and projection,” the content of online-media situation awareness is refined. The perception layer includes content, time, space, and emotion perceptions. The comprehension layer includes an understanding of the target and hot events. The projection layer includes content burst, spatiotemporal anomaly, and emotional anomaly predictions. Subsequently, a four-level theoretical framework of “data, perception, comprehension, and projection” for online-media situation awareness is constructed, and its theoretical and practical significance is revealed. 2024 Vol. 43 (9): 1046-1058 [Abstract] ( 29 ) HTML (152 KB)  PDF (2025 KB)  ( 37 )

Intelligence Technology and Application

1059 Path Identification and Disruptive Innovation of Technology R&D Based on Analysis of Patent Citation Network Hot! Lu Wanhui DOI: 10.3772/j.issn.1000-0135.2024.09.005 Against the background of the increasingly fierce competition among great powers in terms of international science and technology, scientific and technological advances have become a key factor in the world economic and political competition pattern. Clarifying the subject of technological competition and the path of technological evolution is an important issue for achieving breakthroughs in the paths of technology innovative development. In this study, starting from the path-dependence and technology discontinuity theories, and leveraging patent mining of high-persistence knowledge contribution, identification of the main path of technological evolution and detection of disruptive innovation signals were realized based on the hierarchical perspective of patent citation network. Empirical research and analysis were carried out by taking the field of semiconductor materials as an example. Wide bandgap semiconductor materials are giving rise to a disruptive change in the new generation of power electronics and optoelectronic technology world-wide. By mining the technological evolution path and detecting disruptive innovation signals in the field of semiconductor materials, some technologies in this field with strong signals of disruptive innovation were identified. The results can help the scientific and industrial circles understand the technical fields and provide intelligent support for the development context and layout of technology research and development. The method constructed in this study concerning the path-dependent and disruptive innovation signal detection of technology research and development based on patent citation network analysis also features strong field expansion. 2024 Vol. 43 (9): 1059-1069 [Abstract] ( 31 ) HTML (135 KB)  PDF (1425 KB)  ( 40 )

1070 Research on the Construction of a Scientific and Technical Frontier Detection System Based on Open Source Intelligence Hot! Zeng Wen, Wang Haiyan, Liu Xiaolin, Xiao Yiqing, Zhang Yue DOI: 10.3772/j.issn.1000-0135.2024.09.006 The detection of scientific and technical frontiers is a hot topic in intelligence research, with the aim of using technological means to analyze and predict scientific and technical frontiers and serve scientific and technical management. The new information environment has brought about changes and challenges to intelligence production, and the effective utilization of open-source information to provide more comprehensive intelligence services has been increasingly valued by intelligence research scholars. However, the analysis and depiction of intelligence have entered a new stage accompanied by the development of technology. This study constructed a scientific and technical frontier detection systems to explain the basic elements and key technologies based on open-source intelligence. It explores the feasibility of intelligent engineering construction for analyzing and depicting scientific and technical frontiers, and provides a reference for intelligence research. 2024 Vol. 43 (9): 1070-1079 [Abstract] ( 23 ) HTML (106 KB)  PDF (5315 KB)  ( 50 )

1080 Comprehensive Analysis of Data Characteristics in Chinese Academic Papers Mentioned on WeChat Hot! Yu Houqiang, Li Longfei, Yang Siluo DOI: 10.3772/j.issn.1000-0135.2024.09.007 Research on the development and application of Chinese altmetric data is limited. This study aims to contribute to the construction of China’s independent knowledge system by investigating the distribution characteristics of numerical values associated with Chinese academic papers mentioned on WeChat. This study presents the distribution characteristics of WeChat mention indicators of all the Chinese academic papers mentioned on WeChat and included in the China National Knowledge Infrastructure (CNKI) in January 2021. The presentation form and timeliness were analyzed along with paper, source, and discipline levels using statistical analysis and data visualization. The main finding of this study is that non-referenced literature accounts for 60.80% of WeChat mentions. Second, the timeliness of WeChat mentions was 56.56%, mainly because scholars shared their research findings at conferences and lectures. Third, the Chinese academic papers mentioned on WeChat official accounts are diverse and scattered. Papers published in core journals are more likely to be mentioned, and the WeChat accounts of journals exhibit noticeable self-mention behavior. Fourth, mentions of academic papers can enhance the professionalism and authority of WeChat articles, promoting their dissemination along with research results, thereby increasing their social impact. 2024 Vol. 43 (9): 1080-1093 [Abstract] ( 28 ) HTML (143 KB)  PDF (3618 KB)  ( 52 )

1094 Named Entity Recognition of Local Chronicles Literature in Traditional Chinese Opera Based on Multi-dimensional Feature Analysis Hot! Zhai Shanshan, Yu Huajuan, Chen Jianyao, Xia Lixin DOI: 10.3772/j.issn.1000-0135.2024.09.008 Local chronicles are a unique and highly valuable form of regional documentation in China. Digitizing and implementing knowledge mining for these records is crucial for the inheritance and dissemination of traditional Chinese culture, as well as for the construction of a culturally strong nation. Named entity recognition (NER) plays a crucial role as a fundamental technology in organizing and discovering knowledge within local chronicles. Although there has been some progress in NER for local chronicles, a systematic technical solution that adapts to the specific features of these texts and the characteristics of domain resources is still lacking. Therefore, this study proposes a novel approach for named entity recognition in traditional Chinese opera local chronicles by integrating multi-dimensional features with Bi-LSTM-CRF. First, by combining syntactic features with textual features such as symbols, suffixes, word structure, context, and negative examples, the distinctive traits of opera entities within local chronicles are analyzed. Thereafter, the Bi-LSTM-CRF model, which performs well in long text structures, is utilized to improve the efficiency of entity recognition with the help of parsed features of opera-like entities. Finally, empirical research is conducted using the specific case of the “Chu Opera Chronicles.” The results demonstrate that the proposed model outperforms the baseline model in terms of named entity recognition, achieving an F1 score of 0.869. 2024 Vol. 43 (9): 1094-1104 [Abstract] ( 15 ) HTML (165 KB)  PDF (1259 KB)  ( 32 )

1105 Study of Short Video Popularity Prediction Based on Network Representation Learning Hot! Zhu Hengmin, Xu Ning, Wei Jing, Shen Chao DOI: 10.3772/j.issn.1000-0135.2024.09.009 Predicting the popularity of short videos not only helps short-video platforms with efficient information management but also plays an important role in monitoring public opinion. Unlike existing studies that focus only on multimodal content features of short videos, to construct a popularity prediction model, we propose a popularity prediction model based on network representation learning, fusing content and network structural features. First, based on the dataset crawled in Douyin, a heterogeneous information network consisting of nodes was constructed, including short videos, publishers, commenters, and edges. After mapping into two different homogeneous networks, namely, short-video and publisher networks, node2vec was selected to represent the network structure in the embedding space as a network modality. Second, the multimodal content features of short videos were extracted and fused using low-rank multiview embedding learning. Finally, a multilayer perceptron machine regression model was proposed for short-video popularity prediction. Comparisons and ablation experiments were further conducted. The results show that fusing network structure features can reduce the error of short-video popularity prediction. The degree of influence of the various modalities on short-video popularity prediction consisted of the textual, network, social, acoustic, and visual modalities, in decreasing order. Our method, which combines short-video content and network structure features, provides new ideas for short-video popularity prediction based on feature engineering. 2024 Vol. 43 (9): 1105-1115 [Abstract] ( 36 ) HTML (118 KB)  PDF (2692 KB)  ( 41 )

Intelligence Reviews and Comments

1116 Research on the Two-Mode Networks in the Field of Library & Information Science: Concepts, Context, and Applications Hot! Wu Jiang, Lin Ping, Huang Xiao, He Chaocheng DOI: 10.3772/j.issn.1000-0135.2024.09.010 Two-mode networks are capable of mining the rich information in many complex network scenarios in a comprehensive, in-depth, and detailed manner. As the network comprising the many research objects in the field of Library & Information Science has a naturally dichotomous property, the application of two-mode networks in this field has yielded better research results. This study provides a systematic overview of the current state of research on two-mode networks in the field of Library & Information Science. First, we define the concepts related to two-mode networks, including affiliation and bipartite networks. Second, the research lineage of two-mode networks is clarified, including the respective research methods, basic processes, and application scenarios. Third, we summarize the logic of applying two-mode networks in fields related to knowledge management and discovery, scientific cooperation and academic evaluation, information dissemination and network public opinion, user needs, and information services. Finally, the research prospects of two-mode networks in the field of Library & Information Science are explored, contributing to the basic method for the construction of a discipline system for information resource management. 2024 Vol. 43 (9): 1116-1128 [Abstract] ( 26 ) HTML (155 KB)  PDF (3723 KB)  ( 41 )