1133 Technical Due Diligence Oriented to Governance Goals Hot! Liu Qiyan DOI: 10.3772/j.issn.1000-0135.2020.11.001 Towards the goal of building a national governance system, this article analyzes and elaborates on the role of technical due diligence in enhancing the modernization of governance capabilities and outlines the development of technical due diligence in terms of technological information business, new service content and its scope, and platform dependencies. The article then observes that technical due diligence will lead to the high-quality development of the science and technology information business, improve the level of scientific and technological management and governance, promote new growth points in technological innovation, and help Chinese technology and products to expand into the international market. The article concludes by offering policy ideas for accelerating the development of the technical due diligence business from three aspects: grasping opportunities, active planning, and multi-channel taking actions. 2020 Vol. 39 (11): 1133-1138 [Abstract] ( 181 ) HTML (54 KB)  PDF (1228 KB)  ( 523 )

1139 Role of Technology Due Diligence in the Development of the Science and Technology Services Industry Hot! Chen Feng DOI: 10.3772/j.issn.1000-0135.2020.11.002 Using a multi-methods approach, including review of literature, symposium, expert interview, and case study, the basic concept and fundamentals of technology due diligence are introduced. The demands and development prospects of the technology due diligence industry and its role in promoting the development of both the science and technology service industry and the science and technology information service of China in the new era are studied. The paper concludes by stating findings and perspectives, such as noting the rapid growth of the technology due diligence industry on the one hand, and observing its role as an engine and multiplier for both the science and technology service industry and the science and technology information service of China on the other hand in the new era. 2020 Vol. 39 (11): 1139-1143 [Abstract] ( 192 ) HTML (55 KB)  PDF (870 KB)  ( 584 )

1144 Comparison between Technical Due Diligence and Science and Technology Information and Their Integrated Development Hot! Zhao Kang DOI: 10.3772/j.issn.1000-0135.2020.11.003 With science and technology innovation driving economic development, enterprise technology investment and merger activities are increasing, leading to strong demand for and growth in the technical due diligence business. Beginning with the concept origin, criteria, and trends in technical due diligence, this paper expounds its relevance for the science and technology information service, their referential value for each other, basis of integration, and corresponding applications. 2020 Vol. 39 (11): 1144-1153 [Abstract] ( 161 ) HTML (77 KB)  PDF (2422 KB)  ( 561 )

1154 Identifying the Structure of Disciplines through Journal Author Coupling Analysis Hot! Lu Xiaoli, Wu Dengsheng DOI: 10.3772/j.issn.1000-0135.2020.11.004 Calculating the relationship between journals and identifying their disciplinary structure facilitates the exploration of the interaction characteristics between different disciplines and the analysis of the trends of knowledge flow between disciplines. This paper adopted a journal-author coupling method to identify their disciplinary structure. Tackling the problem of information loss due to the traditional use of binary matrix analysis, this study proposed the idea of directly using a journal-author distribution matrix for cluster analysis. However, the high-dimensional data process problem complicated the cluster analysis of the journal-author matrix clustering process. Therefore, this paper proposed a new clustering method using t-SNE dimensionality reduction and a hierarchical clustering model. 69 economics journals from the CSSCI database were selected to be empirically analyzed. A unique dataset, containing 43,617 papers published from 2014-2018 by 47,458 authors, was constructed. The empirical results demonstrated that the t-SNE + hierarchical clustering model proposed in the paper can effectively process and use the journal-author matrix information. It divided the 69 examined economic journals into 9 categories (sub-fields), and clearly specified the types of different categories. The paper also sorted out the premise and applicable conditions of the journal author coupling method to identify the disciplinary structure. 2020 Vol. 39 (11): 1154-1161 [Abstract] ( 153 ) HTML (88 KB)  PDF (2749 KB)  ( 583 )

1162 Knowledge Flow between International Patent Classification Numbers and Knowledge Spillover Measures between Technology Sectors: Based on China??s Authorized Patent Data Hot! Wang Gege, Liu Shulin DOI: 10.3772/j.issn.1000-0135.2020.11.005 The new economic growth theory emphasizes the contribution of knowledge spillovers to economic growth. However, measuring knowledge spillovers has been a major challenge for economists due to its intangibility. With the advantage of big data, this paper analyzes knowledge spillovers by building a technical spillover matrix using the data of more than 300,000 of China’s authorized inventions that are in the incoPat Global Patent Database. This matrix uses the patents’ different IPC numbers to represent the knowledge flow between different technical fields. The main IPC number indicates the source technology field, the remaining sub IPC numbers represent the receiving technology field, and the four-digit IPC number is used to divide the technical sub-fields. The research discovers the externality of the knowledge spillover effect and identifies the direction, width, and intensity of the spillover among technologies. Consequently, the heterogeneity of the knowledge spillover in different technology fields is revealed. The conclusion of this paper can provide some theoretical support to the government’s subsidy policy for technology innovation. 2020 Vol. 39 (11): 1162-1170 [Abstract] ( 143 ) HTML (186 KB)  PDF (1483 KB)  ( 596 )

1171 Research on Identification of Potential Competitors Based on the Semantic Analysis of Patent Specification Hot! Shi Min, Luo Jian, Cai Lijun DOI: 10.3772/j.issn.1000-0135.2020.11.006 Based on the semantic analysis of patent specification, the research of potential competitor identification can help enterprises determine strong competitors early on, provide information for strategic decision-making, and enrich the research theory of potential competitors. The background technology and invention content of the patent specification contain rich market and technical information. A three-dimensional preliminary identification framework of potential competitors, including background similarity, solution similarity, and time axis, is constructed based on the patent specification. Based on LDA semantic analysis technology, this study constructs a potential competitor identification process, including four steps: collecting and preprocessing patent data, building a corpus, initially identifying potential competitors, and confirming potential competitors. Taking the field of water environment as an example, the feasibility and effectiveness of the method are proved. 2020 Vol. 39 (11): 1171-1181 [Abstract] ( 148 ) HTML (114 KB)  PDF (3577 KB)  ( 663 )

1182 High Citation or Zero Citation: Exploring the Optimal Scale of Research Cooperation Based on the Citation of Scientific Publication —Evidence from the Financial Times TOP 45 Journals Hot! Ma Rongkang, Li Zhenzhen DOI: 10.3772/j.issn.1000-0135.2020.11.007 Utilizing the datasets obtained from the Financial Times top 45 journals between 1997 and 2013, this paper examines the relationship between the number of authors and the number of citations a paper received (high citations or zero citation). This study then reveals the optimal scale of research cooperation in the field of business. The results demonstrate the following. First, compared with single-author manuscripts, those involving multiple authors have a considerably positive impact on the total number of citations. Further, the former has a higher probability of being a high-citation paper, while a lower probability of being a zero-citation paper. Second, there is a significant inverted U-shaped relationship between the number of authors and the total number of citations, which is in accordance with the relationship between the number of authors and the probability of being high-citation papers. However, the relationship between the number of authors and the probability of zero-citation papers is also U-shaped. The optimal number of authors that results in a high-citation paper in the field of business is approximately three authors. Finally, the optimal number of authors coordinating to publish a paper in the field of business in term of high-citation and zero-citation papers gradually increases from 2-3 to 3-4 with time. 2020 Vol. 39 (11): 1182-1190 [Abstract] ( 151 ) HTML (130 KB)  PDF (1231 KB)  ( 562 )

1191 Propensity Score Matching: Facilitating the Causal Inference of Data Science-Oriented Information Studies Hot! Wang Xiaolun, Zhao Yuxiang, Wang Yuefen DOI: 10.3772/j.issn.1000-0135.2020.11.008 In the era of big data, data science-oriented quantitative research in the information science field must go beyond analysis of correlation to analysis of causality, and more effectively mine data value and expand new quantitative methods in information studies. This article introduces a statistical method for measuring treatment effects based on secondhand or observational data, called propensity score matching (PSM). First, we introduce the implementation steps of PSM to clarify the method’s origins and principles. Second, we discuss the need for controlled experiments and causal inference in the field of data science-oriented quantitative information studies, and emphasize the advantages and contributions of PSM. Third, we conduct an in-depth review of existing work employing the PSM approach in both information science and related fields, and elaborate upon directions for future research applying PSM in information science. Finally, we describe the future prospects and challenges of this method in the field of information science. This study thus sheds light on the quantitative area of information science from a data science perspective. 2020 Vol. 39 (11): 1191-1203 [Abstract] ( 398 ) HTML (159 KB)  PDF (2219 KB)  ( 1289 )

1204 Development Trends of Science Discipline: Five-Dimension Analysis Method Hot! Zhang Chaoxing DOI: 10.3772/j.issn.1000-0135.2020.11.009 Development trends in the discipline of science are crucial for intelligence analysts to grasp the status of science and technology and for policymakers to make the right policy decisions. According to articles on development trends in the discipline of science published by China National Knowledge Infrastructure (CNKI), there are no unified and reliable methods to follow in this field. Based on published related articles, this paper proposes five dimensional directions that should be considered in the process of analysis of the development trend, namely the five-dimension method: object dimension, carrier dimension, data dimension, time dimension, and method dimension. The reasons for different choices in this dimension and their corresponding possible outcomes are compared. Furthermore, in combination with the author??s work experience in this field, corresponding selection suggestions are offered. 2020 Vol. 39 (11): 1204-1213 [Abstract] ( 422 ) HTML (101 KB)  PDF (1583 KB)  ( 573 )

1214 User Profile Tag Generation and Information Recommendations for Science and Tencnology Intelligence Hot! Zhao Hui, Hua Bolin, He Hongwei DOI: 10.3772/j.issn.1000-0135.2020.11.010 Science and technology management departments are important users of science and technology intelligence. Actively understanding the intelligence needs of science and technology management departments has become a vital aspect of providing accurate intelligence services in the era of big data. The user portrait approach enables and simplifies this process. Through multi-source data collection and analysis, intelligence users are tagged with labels to describe their characteristics and needs, and recommendations are generated accordingly. This paper uses five methods related to natural language processing to generate labels and extract keywords from text: direct extraction, word pair matching, subject word extraction, generation scheme based on TF-IDF, and combinatorial word processing. After generating labels, a word forest table is used to analyze their association and similarity. Collaborative filtering, common sense, tag association, and other recommendation algorithms are then employed to recommend labels for different users, and preliminary user portraits are constructed. This study’s empirical research and findings show that this set of methods can effectively outline the information needs and characteristics of science and technology management departments. Furthermore, the recommended content is illuminating for science and technology intelligence work. 2020 Vol. 39 (11): 1214-1222 [Abstract] ( 248 ) HTML (100 KB)  PDF (2070 KB)  ( 1276 )

1223 Relevance between Image and Text of Social Media Posts for Disasters Hot! Li Gang, Zhang Ji, Mao Jin, Ma Chao DOI: 10.3772/j.issn.1000-0135.2020.11.011 In this study, we understand the relevance between the images and the texts of Weibo during disasters via images and texts analyses. Considering posts related to typhoon mangosteen as research objects, we developed a text and text relevance classification model based on the image semantic understanding framework. This was done using deep and machine learning methods to build a classification model after extracting the features of the images and texts. The deep learning method is superior to the traditional machine learning method when implementing the text and relevance classification task. The experimental data contain information regarding a single type of disaster; however, the annotation data are not used effectively to ensure the consistency of the data. The classification model helps understand the content of microblog during disasters, and the deep learning model can better classify the relevance between the images and the texts. 2020 Vol. 39 (11): 1223-1231 [Abstract] ( 254 ) HTML (86 KB)  PDF (3200 KB)  ( 659 )

1232 A Review of Digital Divide Research Abroad Hot! Xu Fang, Ma Li DOI: 10.3772/j.issn.1000-0135.2020.11.012 In recent years, digital divide research has attracted extensive attention from scholars worldwide. The purpose of this paper is to provide a reference for Chinese scholars to understand the status quo of foreign research on digital divide and to carry out further systematic research in this field. First, this paper systematically summarizes the concept, the types of digital divide, and the problem domains of digital divide research. These domains include its influencing factors, measurement indexes, evaluation models, measures to bridge the gap, and development trends by means of synthesis, induction, and comparison. Then, the contemporary context of digital divide research abroad is reviewed. The review reveals that a relatively systematic theoretical system has been formed and the research methods in digital divide research are mainly quantitative research, which implies qualitative research in this field needs to be strengthened. Additionally, relevant research on the third digital divide is still in the preliminary stage, and the classification of digital divide and the measures to bridge the digital divide require further study. Last, the review indicates that the development trend of digital divide research is digital inclusion. 2020 Vol. 39 (11): 1232-1244 [Abstract] ( 340 ) HTML (187 KB)  PDF (1439 KB)  ( 1192 )