549 Constructing a Scientific and Technological Intelligence Theoretical System in a Complex Information Environment Hot! Zhao Zhiyun, Zeng Wen DOI: 10.3772/j.issn.1000-0135.2022.06.001 Since its birth, China's scientific and technological intelligence business has been closely related to the pulse of national construction and development; it has continued to grow and develop with the advancement of science and technology. The new competitive condition of global science and technology and the new requirements of the national “14th Five-Year Plan” have presented opportunities for developing scientific and technological intelligence and raised new questions for its theoretical exploration. This study follows the logical clue of “the combination of historical mirror and practical analysis, and the unity of theoretical construction and application effectiveness.” On the basis of a summary and analysis of the research status of scientific and technological information theory, this study analyzes the requirements and research composition of the theoretical exploration of scientific and technological intelligence in a complex information environment; it proposes the construction assumptions and quality standards for a scientific and technological intelligence theoretical system. 2022 Vol. 41 (6): 549-557 [Abstract] ( 495 ) HTML (68 KB)  PDF (935 KB)  ( 407 )

558 The Characteristic, Principle and Method of Collaborative Construction of Context Ontology Based on Concept Lattice Integration in Context-Aware System Hot! Jiang Yongchang, Man Xiaoli, Wang Honglu DOI: 10.3772/j.issn.1000-0135.2022.06.002 To build a context-aware system (CAS) in the collaborative construction of context ontology (COnt) of heterogeneous resources and environmental dynamic information in various fields, it is essential to provide accurate context aware services for users’ decision-making. Therefore, based on the similarity of concept lattice and COnt, the necessity, uniqueness and feasibility of integrated realization, this paper theoretically distributes and integrates the two types of context resources of the system based on the context life cycle. It is proposed that the former can obtain unified domain COnt modeling and network constraint representation in the hierarchical structure of its concept lattice integration based on knowledge creation reality three-dimensional abstraction, and the latter can obtain the context awareness meta-ontology (CAMOnt) modeling and problem solving oriented instantiation creation in the human-machine interaction cognition of context-aware middleware based on visualization of the users' actual application situation by the conceptual lattice deconstruction of domain COnt and its reconstruction through “5Ws1H” awareness association with environmental resources. Considering the evolution of fire emergency domain COnt to fire rescue CAMOnt as an example, the analysis shows that CAS can be effectively established in this COnt collaborative construction method and provides users with accurate context-aware services. 2022 Vol. 41 (6): 558-573 [Abstract] ( 329 ) HTML (168 KB)  PDF (3072 KB)  ( 520 )

574 Profiling Attribution on the Label of Scientific Research Institutions Based on the Ontology Model Hot! Guo Hongmei, Zeng Jianxun DOI: 10.3772/j.issn.1000-0135.2022.06.003 Scientific research institutions are important objects of scientific research management and evaluation as well as important units of resource organization. With the development of Chinese science and technology, scientific research outputs have increased exponentially while scientific research activities have attained a wide range and diverse forms. Appropriately determining the characteristics of scientific research institutions from the massive scientific research results and identifying the related institutions from complex social networks have always been a concern of the scientific research community. Institutional profiling can help in understanding the institution, assisting scientific research planning and management decision-making, and identifying future partners and competitors. The study aimed to profile and identify the attributes and related institutions of scientific research institutions based on the ontology model. It selected the subject category and industry category attributions to discuss the process of labeling the attributes of scientific research institutions. Further, it selected cooperative and benchmarking institutions to discuss the process of identifying closely related institutions in the intricate network. 2022 Vol. 41 (6): 574-583 [Abstract] ( 227 ) HTML (91 KB)  PDF (1454 KB)  ( 480 )

584 Burst Term Detection Study Based on Multi-Indicators Hot! Peng Guochao, Kong Yongxin, Wang Yuwen DOI: 10.3772/j.issn.1000-0135.2022.06.004 Since burst terms are forward-looking and informative, burst term detection (BTD) helps to predict research fronts and hotspots in certain subject areas. In this study, we build a multi-indicator system for BTD, including burst indicators (“random,” “growth,” and “burst”), knowledge fusion indicators, and influence indicators. Based on “random” and “growth,” three categories of burst terms are clustered by K-means, namely, emergence terms, strong burst terms, and weak burst terms. Combining the burst indicators, knowledge fusion indicators, and influence indicators, the burst terms with different developmental statuses were identified. The results show that emergence terms with a high burst can gain more attention and have more influence at the initial stage. Burst terms with a high degree of knowledge fusion indicate that the breadth and intensity of fusion are higher, and they are more likely to develop into research hotspots in the future. Finally, burst terms with high influence indicates that they receive wide attention and have a certain research base and have a higher probability to become a research frontier in the future. 2022 Vol. 41 (6): 584-593 [Abstract] ( 247 ) HTML (181 KB)  PDF (1601 KB)  ( 549 )

594 Research on the Governance Path of the Public Opinion Reversal of Emergency: Based on Information Interaction Perspective Hot! Cong Jingyi, Ai Wenhua, Hu Guangwei DOI: 10.3772/j.issn.1000-0135.2022.06.005 The reversal of public opinion in public emergencies brings great challenges to social stability and government credibility. With the support of social media, information interaction has become an important factor affecting public opinion and sentiment trends. Research on the effectiveness of public opinion reversal governance from the perspective of information interaction provides an important decision-making reference for the public opinion governance and control in the event of public emergencies. By constructing an evolution modelSFEnInRfrom the perspective of information interaction, this study simulates the competitive evolution of an unknown event population S, an opinion presenter Ii with opinion i, a potential opinion presenter Ei with opinion i, followers F holding a wait-and-see attitude, and an individual R with no interest in the event on the social network. Then, it analyzes the characteristics of the system evolution under different attitude scenarios, solution strategies, and measures. The results show that the timing of announcements can effectively affect the evolution of netizens’ opinions. Improving information transparency and objective reporting can accelerate the return of netizens to a rational state. The public opinion system can actively guide netizens and reduce the spread of extreme and radicalized public opinions. 2022 Vol. 41 (6): 594-608 [Abstract] ( 470 ) HTML (286 KB)  PDF (4753 KB)  ( 408 )

609 Technology Convergence Prediction by the Semantic Representation of Patent Classification Sequence and Text Hot! Zhang Jinzhu, Li Yifeng DOI: 10.3772/j.issn.1000-0135.2022.06.006 A technology convergence prediction method based on the semantic representation of patent classification sequence and text is proposed to enrich the network and text semantic representation of patent classification, realize their more effective semantic fusion, and improve the effect of technology convergence prediction. First, the semantic representation of the patent classification sequence is directly carried out, and a technology convergence prediction method based on the semantic representation of the patent classification sequence is proposed, considering the location and context of patent classification. Second, the patent classification text allocation method is designed according to the ranking importance of patent classification in the sequence while the technology convergence prediction method is formed based on the semantic representation of patent classification text. Then, a multi-feature fusion method and a technology convergence prediction method combining patent classification sequence structure and the semantic representation of text content are proposed. Finally, based on the theory and method of link prediction, the proposed multi-technology convergence prediction methods are quantitatively evaluated. Experiments in the unmanned aerial vehicle field confirm that the effect of the patent classification sequence semantic representation model is better than other network representation learning methods. The text assignment method of patent classification by importance is better than the average text distribution method, which can better predict technology convergence. In the semantic fusion model, “Support Vector Machine + Hadamard Product” has the best performance, which is better than the single patent classification sequence and the patent classification text method. The method used in this study can better predict the possible technology convergence and provide better reference for technology layout and technology research and development. 2022 Vol. 41 (6): 609-624 [Abstract] ( 483 ) HTML (198 KB)  PDF (1639 KB)  ( 521 )

625 Effects of Online Surrogate Health Information Seeking on Health Behaviors and Health Levels of Supported People Hot! Song Xiaokang, Zhao Yuxiang, Zhu Qinghua DOI: 10.3772/j.issn.1000-0135.2022.06.007 Surrogate Health Information Seeking, which is based on interpersonal cooperation, has become a common phenomenon in the Internet environment. This study considers the digital immigrant group as the research object, and applies the propensity score matching method to study the effects of online surrogate health information seeking on the health behaviors and health levels of the supported people. In this study, 1063 valid data were collected by a questionnaire survey. A logistic regression model was used to calculate the propensity score of the covariates. Based on the propensity score, the participants were matched into the experimental and control groups. Subsequently, by calculating the value of the average treatment effect, the causal relationships between surrogate health information seeking and health behaviors and health levels were analyzed. Simultaneously, the reliability of the research results was ensured through a balance test and sensitivity analysis. The results showed that surrogate health information seeking has a positive impact on the diet behavior and mental health level of the supported people. However, it has no significant impact on the exercise behavior and physical health level. The results facilitate the further understanding of the role of surrogate health information seeking behavior and provide a reference for government departments and public health institutions to carry out surrogate health information seeking related practical activities. 2022 Vol. 41 (6): 625-636 [Abstract] ( 421 ) HTML (184 KB)  PDF (1021 KB)  ( 467 )

637 Review of the Research Progress on the Open Scientific Datasets Unified Discovery Platform Hot! Luo Pengcheng, Wang Jimin, Nie Lei DOI: 10.3772/j.issn.1000-0135.2022.06.008 In the open scientific environment, the reuse of scientific data is valued. To help researchers find data, many unified discovery platforms for scientific datasets have been launched. Accordingly, dataset retrieval methods have received great attention from researchers. This study conducts an extensive review of the research and applications related to the unified discovery platform of open scientific datasets at home and abroad. It surveys the research progress through dataset collection, dataset organization, dataset retrieval, and retrieval results ranking and further analyzes the future research directions. Specifically, we provide a detailed introduction and in-depth analysis of dataset collection methods, multi-source metadata unified methods, metadata quality analysis, metadata information enrichment methods, query expansion, and ranking methods as well as relevance criteria and comprehensive ranking methods. This review is expected to act as a reference to further research and applications. 2022 Vol. 41 (6): 637-650 [Abstract] ( 334 ) HTML (197 KB)  PDF (999 KB)  ( 650 )

651 Misinformation Detection in Social Media Hot! Wu Shiyuan, Dong Qingxing, Song Zhijun, Zhang Bin DOI: 10.3772/j.issn.1000-0135.2022.06.009 Social media has dramatically improved the efficiency of information access, but it has also contributed to the generation and dissemination of misinformation on the Internet. The accurate and quick detection of misinformation to improve the online information environment is an important issue. Inspired by the Information Ecology Theory, this paper expounds on the current problems and relevant detection methods of misinformation from the three perspectives of content, users, and dissemination. Existing detection methods have achieved state-of-the-art results by deep learning methods. However, because of the lack of relevant data in the early stages, studies on the early detection of misinformation are still rare. Additionally, large-scale benchmark datasets for transfer learning and pre-training tasks are yet to be constructed. Moreover, information mining from users needs to be further evaluated. 2022 Vol. 41 (6): 651-661 [Abstract] ( 361 ) HTML (147 KB)  PDF (1293 KB)  ( 800 )