Abstract
Objective: Research takes the methodological knowledge in the full text of academic literature as a knowledge production element, and divides it into four categories: Theory &Method, Data, Model, and Tool & Software. Identify the complex network characteristics of scientific research collaboration in economic management field driven by it, in order to achieve efficient promotion of knowledge production. Methods: Develop a crawler by python, and uses CNKI as data source to obtain the full text data of 5,564 papers (about 50,076,000 characters) from 2000 to 2019 in “Management World”, then combines the TF-IDF, fusion rules and manual annotation to extract 6946 records of methodological knowledge data and its subsidiary information. The relationship were visualized by Gephi, and characteristics are analyzed. Results/Conclusions: The overall collaboration network and scientific research institutions driven by Theory &Method are the most complexity and multi-mode (complete and continuous development model are included), while it has a cohesive collaborative subnet. Methodological knowledge-driven scientific research collaboration networks have different characteristics: Theory & Method driven has the highest complexity, a long duration, and much more mature in economics and management field. The network formed by institutions has a low density, means a cross-institutional, large-scale collaboration model has not yet been formed, which may be restricted by geographical factors and research topics. Among the four types of methodological knowledge, the Theory &Method and Data type drive the research collaboration of institutions more obviously. Limitations: The types and numbers of data sources in this study need to be expanded, and the extraction of specific methodological knowledge for the full text of academic literature needs to be further expanded by relying on machine learning and other methods.
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References
Li, G., Li, C., Li, X.: Research on the discovery of scientific research teams based on social network analysis. Libr. Inf. Serv. 58(07), 63–70, 82 (2014)
Pan, X.: Research on automatic extraction of software entities and academic influence. Nanjing University (2016)
Xu, H., Zhu, X., Zhang, C., et al.: Analysis and design of methodological knowledge extraction system for full text of academic documents. Data Anal. Knowl. Disc. 3(10), 29–36 (2019)
Wang, F., Zhu, N., Zhai, Y.: The application of hybrid methods in China’s information science research and the analysis of their field distribution. J. Inf. 36(11), 1119–1129 (2017)
Wang, Y., Zhang, C.: Using the full-text content of academic articles to identify and evaluate algorithm entities in the domain of natural language processing. J. Informetr. 14, 101091 (2020)
Wang, Z.: Research on the application of social network analysis methods in scientific research collaboration networks. Dalian University of Technology (2006)
Ye, G., Xia, L.: Analysis of cross-regional scientific research collaboration model. J. Libr. Sci. China 45(03), 79–95 (2019)
Yeh, Yu, Z., Qian, L.: Multidimensional effects of proximity between the US cities of research collaboration. Inf. Theory Pract. 43(11), 86–91 + 27 (2020)
Wen, W., Ding, K., Zhu, Z.: Scientific cooperation network of China’s major research institutions in the analysis - based on Web of Science study. Res. Sci. 28(12), 1806–1812 (2010)
Chai, Y., Liu, C., Wang, X.: The construction and characteristic analysis of China’s university scientific research cooperation network —— based on the data of “211” universities. Libr. Inf. Serv. 59(02), 82–88 (2015)
Zhao, R., Wen, F.: Research collaboration and knowledge exchange. Libr. Inf. Serv. 55(20), 6–10, 27 (2011)
Wang, C.: Research on the influencing factors of university teachers’ scientific research cooperation: taking Guangxi as an example. Sci. Technol. Prog. Policy 29(21), 145–149 (2012)
Xu, H., Huang, C., Jin, W., et al.: Research hotspots in subject areas and pattern recognition of scientific research collaborations —— taking Chinese literature in the field of acoustics in China as an example. Jiangsu Sci. Technol. Inf. 37(19), 13–16 (2020)
Gao, X., Chen, K.: Complex network analysis of the evolution characteristics of cooperative innovation network structure. Sci. Res. Manage. 36(06), 28–36 (2015)
Wang, J., Hou, H., Fu, H., et al.: Author cooperation network structure and group differences in the tripartite relationship analysis. Libr. Inf. Serv. 62(09), 102–111 (2018)
Wang, F., Shi, H., Ji, X.: Application of theory in information science research in China: based on the content analysis of “Journal of Information.” J. Inf. 34(06), 581–591 (2015)
Gephi. https://gephi.org/
Li, L.: Research on the research collaboration network —— based on the perspective of social network theory. Huazhong Agricultural University, Hubei (2011). https://doi.org/10.7666/d.y2003857
Peng, X., Zhu, Q., Shen, C.: Analysis of author cooperation in the field of social computing based on social network analysis. J. Inf. 32(03), 93–100 (2013)
Wang, H., Yu, C., Zhao, P.: The duality of consumer ethnocentrism and its market strategic significance. Manage. World 02, 96–107 (2005)
Wang, H., Zhao, P.: Research on market segmentation based on consumer ethnocentrism. Manage. World (05), 88–96, 156 (2004)
Wang, Y., Yu, C., Zhao, P.: The relationship between the consumer model of brand equity and the product market output model. Manage. World 01, 106–119 (2006)
Acknowledgements
The research was supported by Jiangsu Provincial Social Science Foundation Youth Project: Research on the recommendation strategy of electronic literature resources integrating online academic social information (No. 21TQC003); the University Philosophy and Social Science Research Project of Jiangsu province (No. 2019SJA2274); Innovation Fund General Project I of Nanjing Institute of Technology (No. CKJB202003); Major Project of Philosophy and Social Science Research in Universities of Jiangsu Provincial Department of Education (No. CKJA201706); National College Student Practice Innovation Training Program Project of Nanjing Institute of Technology (No. 202011276021Z).
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Xu, H. et al. (2022). Methodology-Driven Characteristics of Scientific Research Collaboration Networks in the Field of Economic Management: Mining and Analysis Based on Big Data. In: Tian, Y., Ma, T., Khan, M.K., Sheng, V.S., Pan, Z. (eds) Big Data and Security. ICBDS 2021. Communications in Computer and Information Science, vol 1563. Springer, Singapore. https://doi.org/10.1007/978-981-19-0852-1_25
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