Analysis of Knowledge Flow Based on Academic Social Networks: A Case Study of ScienceNet.cn
Xiaolan Wu1,2,Chengzhi Zhang2()
1School of Management Science and Engineering, Anhui University of Finance and Economics, Bengbu 233030, China 2School of Economics and Management, Nanjing University of Science and Technology, Nanjing 210094, China
[Objective] This study aims to explore the knowledge flow on academic social networks. [Methods] Take ScienceNet.cn as the representative, we first collect all the data about users’ research directions and friends. Then, we use the simple correlation coefficient to measure the distribution relation of knowledge flow of different disciplines users, and adopt Louvain algorithm to detect the community structure among first-level disciplines. [Results] It is found that the knowledge flow of different disciplines is similar to each other through simple correlation coefficient. There are four knowledge-flow communities among first-level disciplines detected by Louvain algorithm. [Limitations] We construct knowledge flow network only based on friends’ relationship, without considering comments and recommendation relationship. [Conclusions] Through our research, we find that “Life Science” and “Medical Science” showed the most obvious disciplinary affinity in ScienceNet.cn. In addition, there are four main knowledge flow paths cross discipline departments, such as “Earth Science - Life Science - Medical Science”, “Chemical Science - Engineering Material - Mathematical Science-Information Science”, “Earth Science - Engineering Materials”, “Information Science - Management Science”.
吴小兰,章成志. 学术社交媒体视角下学科知识流动规律研究*——以科学网为例[J]. 数据分析与知识发现, 2019, 3(4): 107-116.
Xiaolan Wu,Chengzhi Zhang. Analysis of Knowledge Flow Based on Academic Social Networks: A Case Study of ScienceNet.cn. Data Analysis and Knowledge Discovery, 2019, 3(4): 107-116.
(Xu Xiaoyi, Yang Liying.Metholgoy Research of Disciplinary Knowledge Flows in Scientific Collaboration: A Case of “Pharmaceutical Chemistry” Discipline[J]. Library and Information Service, 2014, 58(19): 83-91.)
(Wu Jiang, Jin Miao, Chen Jun.Construction and Analysis of Interdisciplinary Knowledge Flow Network Based on Co-occurences of Funding Application Codes[J]. Library and Information Service, 2016, 60(8): 79-85.)
[4]
Cronin B, Meho L I.The Shifting Balance of Intellectual Trade in Information Studies[J]. Journal of the American Society for Information Science & Technology, 2008, 59(4): 551-564.
(Zhou Qiuju, Yang Liying, Yue Ting, et al.Exploring the Subject Structure and Knowledge Flow Based on Journal Co-citation Network and Inter-citation Network[J]. Journal of Information, 2014, 33(8): 84-91.)
(Zhao Xing, Tan Min, Yu Xiaoping, et al.Exploring the Citation Networks for Knowledge Diffusion of Humanities and Social Sciences in China[J]. Journal of Library Science in China, 2012, 38(5): 59-67.)
[7]
Chua A Y K, Yang C C. The Shift Towards Multi-Disciplinarity in Information Science[J]. Journal of the American Society for Information Science and Technology, 2008, 59(13): 2156-2170.
(Qiu Junping, Cao Jie.Research on Knowledge Diffusion Among Different Disciplines——Take Library and Information Science for Example[J]. Information Studies: Theory and Application, 2012, 35(10): 1-5.)
(Zeng Qian, Yang Siluo.A Comparative Study of Knowledge Exchange Between Library and Information Science at Home and Abroad: From the Perspective of Citation Analysis[J]. Information Studies: Theory and Application, 2013, 36(10): 114-119, 108.)
[10]
Yan E.Finding Knowledge Paths Among Scientific Disciplines[J]. Journal of the Association for Information Science & Technology, 2014, 65(11): 2331-2347.
[11]
Tang L.Does “Birds of a Feather Flock Together” Matter—Evidence from a Longitudinal Study on US-China Scientific Collaboration[J]. Journal of Informetrics, 2013, 7(2): 330-344.
(Xu Xiaoyi, Yang Liying.Analysis of Disciplinary Knowledge Flows Network Based on Coauthored Papers: A Case of Medicinal Chemistry Discipline[J]. Library and Information Service, 2015, 59(1): 89-98.)
[13]
Coleman A S.Academic Blogs[J]. Reference Librarian, 2005(3):10-17.
(Hu Changping, She Jingjing, Shao Qigan.Research on the Innovative Knowledge Transferring in Academic Blog[J]. Journal of Information, 2008, 27(5): 3-6.)
(Jia Xinlu, Wang Yuefen. The Concept, Characteristics and Research Hotspots of Academic Social Networks[J]. Research on Library Science, 2016(5): 7-13.)
[16]
Oh J S, Jeng W.Groups in Academic Social Networking Services—An Exploration of Their Potential as a Platform for Multi-disciplinary Collaboration[C]// Proceedings of the 3rd International Conference on Privacy, Security, Risk and Trust. 2011.
[17]
Jiang J, Ni C, He D, et al.Mendeley Group as a New Source of Interdisciplinarity Study: How Do Disciplines Interact on Mendeley?[C]// Proceedings of the 13th ACM/IEEE-CS Joint Conference on Digital libraries. 2013.
(Wang Xiaoguang.Information Communication in Blog Community: An Empirical Analysis of Web Links[J]. Journal of the China Society for Scientific and Technical Information, 2009, 28(2): 248-256.)
[19]
Newman M E J, Girvan M.Finding and Evaluating Community Structure in Networks[J]. Physical Review E, 2004, 69(2): Article No. 026113.
(Qiu Junping, Wang Feifei.Anaysis About Knowledge Communication Network Based on Friends Link in the Blog Community——A Case Study of the Blog Community in www.sciencenet.cn[J]. Documentation, Information and Knowledge, 2011(6): 25-33.)
