447 Knowledge Transfer Model of a Network Q&A Community: An Empirical Analysis Based on the AskMe Portion of MetaFilter Data Hot! Xia Lixin, Yang Jinqing, Ye Guanghui, Cheng Xiufeng DOI: 10.3772/j.issn.1000-0135.2019.05.001 To explore the influencing factors and mechanisms of user knowledge transfer in Q&A community networks, this study proposes a knowledge transfer model for Q&A communities by introducing social network analysis (SNA). This study first analyzes the interpersonal knowledge network structure of the MetaFilter Q&A community while considering net density, structural holes, central potential, average shortest path, and the clustering coefficient of SNA. The study then inspects the structures of the following four types of networks and their effects on knowledge transfer in the Q&A community: strong-and-sparse ties, weak and tight ties, strong and tight ties, and weak and sparse ties. The results of the study indicate the following. (1) Both strong-and-sparse and weak-and-tight ties networks contribute to knowledge transfer in a Q&A community. (2) When the restrictiveness of structural holes is lower and the network is sparser, users can more easily gain access to heterogeneity knowledge sources, and the average shortest path is shorter. In addition, the small-world effect is more obvious, and users can more effectively exchange knowledge. The clustering coefficient has a two-part effect in which it is neither higher nor lower. When it approximates the results of the entire network, it contributes to knowledge transfer. Furthermore, a higher central potential indicates that the relations of users are very close, and thus it has a greater influence on knowledge transfer. (3) Although the SNA index has a decisive role in knowledge transfer, some indices have a joint effect. An efficient network may still have several low indices. In summary, this study explores the influence of different network structures on knowledge transfer to enable network structures to be adjusted based on index coefficients, thereby improving the efficiency of knowledge transfer on Q&A communities. 2019 Vol. 38 (5): 447-457 [Abstract] ( 274 ) HTML (141 KB)  PDF (2945 KB)  ( 809 )

458 Factors Affecting Citations of Monographs in Chinese Humanities and Social Sciences： The Role of Punctuation Marks Hot! Ruan Xuanmin, Lyu Dongqing, Cheng Ying, Ke Qing DOI: 10.3772/j.issn.1000-0135.2019.05.002 The title is an important part of monographs. It plays a significant role in summarizing the main content and attracting readers. This paper used monographs indexed in CBKCI and published between 1999 and 2009 to examine whether punctuation features such as the presence of punctuation as well as point and labelling marks, the combination and number of punctuation marks, and the structure of the title influence the number of times monographs are cited. Nonparametric tests and multiple linear regression analysis were used. The results showed the following. (1) Compared with plain text titles, correct use of punctuation in the title increased citations. Monographs whose title included labelling marks only or both labelling marks and point marks received more citations. The number of punctuation marks had no effect on citations. (2) The presence of a colon in the title increased citations of monographs. Titles with a slight pause mark were cited more than those without. Conversely, when the title included a punctuation mark used to enclose only the title of a book, the monograph had fewer citations. (3) Monographs with a compound title received more citations than those without. 2019 Vol. 38 (5): 458-472 [Abstract] ( 185 ) HTML (248 KB)  PDF (909 KB)  ( 560 )

473 The Impact of Innovation Subject Types on the Award-Winning Patent Utilization Ability in China Hot! Qiao Yongzhong, Deng Siming DOI: 10.3772/j.issn.1000-0135.2019.05.003 This study takes the “China Patent Award” project as the sample and considers region and innovation subject type as categorical variables. After confirming the dependence between the two variables and the significant correlation between the types of innovators and the application of the awarded patents, the following conclusions are drawn. In various regions, the overall application of awarded patents basically maintains the same level, as well, the awarded number is not the key factor to influence their implementation and application. In addition, the innovation subjects with the highest application rate of awarded patents in different regions are different—universities in the eastern region, cooperation subjects in the central region, enterprises and government organizations in the western region, and individual and research institutes in the northeastern region. 2019 Vol. 38 (5): 473-481 [Abstract] ( 169 ) HTML (146 KB)  PDF (771 KB)  ( 470 )

482 Research on Construction of a Subject Knowledge Base based on Literature Knowledge Extraction: Using the Knowledge Base of Activating Blood Circulation and Removing Stasis as the Object Hot! Ma Yumeng, Wang Fang, Huang Jinxia, Jiang Enbo, Zhang Xiyu DOI: 10.3772/j.issn.1000-0135.2019.05.004 Researchers put forward higher requirements for efficient acquisition and utilization of domain knowledge in the big data era. As literature is an effective way for researchers to quickly and accurately understand the research situation in their field, knowledge discovery based on literature has become a new research method. As a tool to organize and manage knowledge in a specific domain, the subject knowledge base can be used to mine and present the knowledge behind the literature to meet users’ personalized needs. This paper designs the construction route of the subject knowledge base for specific research problems. An information extraction method based on knowledge engineering is adopted. First, a subject knowledge model is built through abstraction of the research elements. Then, under the guidance of the knowledge model, the knowledge extraction strategy of each model node is developed to analyze, extract, and correlate entities, relations, and attributes in the literature. Finally, a database platform based on this structured knowledge is developed that can provide a variety of services such as knowledge retrieval, knowledge browsing, knowledge Q&A, and visualization correlation. Taking construction practices in the field of activating blood circulation and removing stasis as an example, this paper analyzes how to construct a subject knowledge base based on literature knowledge extraction. As the system functional test shows, this subject knowledge base can realize the expected service scenarios such as quick query of knowledge, related discovery of knowledge and literature, and knowledge organization. As this study proposes an effective technical route to building a subject knowledge base to help researchers locate and acquire deep knowledge in literature quickly and accurately, it provides a transformation mode of resource construction and personalized precision services in the data-intensive research environment. 2019 Vol. 38 (5): 482-491 [Abstract] ( 242 ) HTML (96 KB)  PDF (2247 KB)  ( 752 )

492 Research on Crisis Detection in Infectious Disease Surveillance Data Hot! Wang Ping, Mu Dongmei, Gao Hexuan, Fa Hui DOI: 10.3772/j.issn.1000-0135.2019.05.005 As China s informatization process continues to accelerate, infectious disease surveillance systems have accumulated large amounts of accurate data. According to the theories and methods of information science, we can fully mine the intelligence value of information from infectious disease surveillance data. Analysis of this material can provide decision support services for public health management and prevention departments. In particular, this study focused on data from the China Statistical Yearbook of Infectious Diseases, and the China National Bureau Statistics monthly report on infectious disease prevention and control. The process of monitoring and identifying infectious disease crisis events is summarized as “one goal, three objects, three levels of analysis, and three cores.” Another aspect of infectious disease control is building crisis detection/decision support service systems. Theoretical level, this study assesses data integration, information analysis, and crisis detection in infectious disease events. On a practical level, it integrates methods of statistical information analysis with machine learning to establish a forecasting model of epidemic over time. Its aim is promoting theoretical research and practical innovation related to the monitoring, identification, and crisis detection of infectious diseases. 2019 Vol. 38 (5): 492-499 [Abstract] ( 166 ) HTML (98 KB)  PDF (2474 KB)  ( 576 )

500 Scientific Collaboration Recommendation Based on Network Embedding Hot! Yu Chuanming, Lin Aochen, Zhong Yunci, An Lu DOI: 10.3772/j.issn.1000-0135.2019.05.006 This paper researched a scientific collaboration recommendation model in the financial field based on network embedding to promote the formation of a research team in the same research field and improve the efficiency of research. The model integrates two types of network embedding models; one of these is based on the location of vertices, while the other is integrated with network structure. A binary operator for the representation of two vertices was employed to generate a representation of edge. Combining network embedding and machine learning, the model trained a logic regression classifier with the representation of edges as features, and the labels acquired from the classifier were the results of link prediction. By analyzing papers in the financial and physical research fields, several scientific collaboration networks were constructed. The experiments confirm that the proposed integrated model has achieved better performance than single models on the value of AUC, with the efficiency improved by up to 2%; even on a small training set, the value of AUC still reached 60%. The proposed model proved to be feasible in scientific collaboration recommendation, which will effectively promote the formation of a research team in the same field. 2019 Vol. 38 (5): 500-511 [Abstract] ( 356 ) HTML (150 KB)  PDF (1081 KB)  ( 865 )

512 Modeling and Simulation of Knowledge Diffusion in Scientific Collaboration Network Based on a Multi-agent System Hot! Guan Peng, Wang Yuefen, Fu Zhu DOI: 10.3772/j.issn.1000-0135.2019.05.007 It has been proposed that knowledge diffusion in scientific research cooperation networks is affected mainly by knowledge spillover and knowledge innovation. On the basis of this idea, this paper proposes a knowledge diffusion mechanism. This multi-agent system modeling method is used to build a simulation evolution model of knowledge diffusion in scientific research cooperative networks. Thereafter, the influence of network structures, knowledge overflow effects, and individual knowledge innovation ability on knowledge diffusion is analyzed. Through a comparative analysis of evaluation indexes of the knowledge diffusion effect, the following conclusions are drawn. The topology of scientific research cooperation networks has an impact on the knowledge diffusion effect, and a BA scale-free network structure is superior to other network structures (regular network, small world network, random network). The knowledge spillover effect affects mainly the early stage of knowledge diffusion. With the increase in the knowledge spillover efficiency factor, the average network knowledge stock increases in oscillations, the knowledge diffusion rate increases, and the balance degree of network knowledge stock distribution decreases. Individual knowledge innovation ability affects mainly the later stage of knowledge diffusion. Networks with large individual knowledge innovation ability factors show strong average knowledge stock growth, which also aggravates the unbalanced distribution of knowledge stock among individuals. 2019 Vol. 38 (5): 512-524 [Abstract] ( 280 ) HTML (143 KB)  PDF (2594 KB)  ( 606 )

525 The Method for Intelligence Awareness in an Emergency Based on Scenario Similarity Hot! Yang Feng, Zhang Yueqin, Yao Yueye DOI: 10.3772/j.issn.1000-0135.2019.05.008 By combining previous experience intelligence and current real-time intelligence, the implementation method of intelligence awareness in an emergency based on scenario similarity can effectively realize event identification and intelligence judgment of emergencies. This paper elaborates on the idea of intelligence awareness based on scenario similarity, and subsequently proposes an implementation method of intelligence awareness. The implementation method tested the similarity between the scene elements analyzed by the intelligence resource and the characteristic attributes presented by the current emergency. Finally, hazardous chemical accidents were used as examples based on grounding theory, text segmentation, feature word extraction, and similarity calculation. This research finds that the scenario analysis of intelligence resources in an emergency provides a fundamental basis for situation awareness of emergencies in practice. Furthermore, the implementation method based on the scenario similarity test enabled existing intelligence resources to be quickly perceived and offers strong support to subsequent scenario constructions and emergency decisions. 2019 Vol. 38 (5): 525-533 [Abstract] ( 215 ) HTML (132 KB)  PDF (906 KB)  ( 809 )

534 OTSRM-Based Approach for Sentiment Evolution and Topic Analysis Hot! Wang Kai, Pan Wei, Yang Baohua DOI: 10.3772/j.issn.1000-0135.2019.05.009 The sentiment evolution of online public topics plays a very important part in the analysis of public opinion, while current methods have problems such as unclear meanings of sentiment topics and inaccurate evaluation of sentiment evolution. This paper introduced sentiment intensity based on the OLDA model and proposed an Online Topic and Sentiment Recognition Mode (OTSRM). By adding sentiment heritability with a β prior parameter, this model established a sentiment evolution channel and obtained two distribution matrices of feature words and sentiment words. Finally, the relative entropy method was proposed to calculate the maximum value of topic sentiment in adjacent time segments, thereby efficiently identifying the topic sentiment of different texts. The effectiveness of OTSRM was validated using five network datasets and compared with other state-of-the-art models. The experiments showed that our approach achieved good results in the recognition of topic sentiment. 2019 Vol. 38 (5): 534-542 [Abstract] ( 244 ) HTML (157 KB)  PDF (1010 KB)  ( 516 )

543 Influential Factors of the Initial Public Acceptance of Pakistan Government Websites: Dual Perspectives Based on Use Intention and Implementation Intention Hot! Shah Irfan Ali, Wang Fang DOI: 10.3772/j.issn.1000-0135.2019.05.010 Improving the initial acceptance of government websites and developing government websites are key measures taken by the Pakistani government to develop e-government, enhance public credibility, and build a convenient government. Therefore, it is important to explore the factors that influence the initial adoption of government websites by the public. To detail the research, this study adopts the dual-perspectives of user intention and implementation intention. The research results show that the implementation intention has direct effect on the actual use action as well as intermediary effect between the use intention and the actual behavior, and the situation clues have significant influence on the implementation intention. The research findings have theoretical guiding significance for Pakistan to deepen the development of e-government services and build service-oriented government websites. Meanwhile, it will further expand theoretical research on the use of government websites. 2019 Vol. 38 (5): 543-556 [Abstract] ( 212 ) HTML (218 KB)  PDF (977 KB)  ( 765 )