Trend and efficiency analysis of co-authorship network
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- 作者：Shahadat Uddin (1)
Liaquat Hossain (2)
Alireza Abbasi (3)
Kim Rasmussen (4) - 关键词：Co ; authorship network ; Trend analysis ; Efficiency analysis ; Inter ; country collaboration
- 刊名：Scientometrics
- 出版年：2012
- 出版时间：February 2012
- 年：2012
- 卷：90
- 期：2
- 页码：687-699
- 全文大小：477KB
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Liaquat Hossain (2)
Alireza Abbasi (3)
Kim Rasmussen (4)
1. Centre for Complex Systems Research, The University of Sydney, Room 402, PNR Building, Sydney, NSW, Australia
2. Faculty of Engineering and IT, The University of Sydney, Room 335, PNR Building, Sydney, NSW, Australia
3. Faculty of Engineering and IT, The University of Sydney, Room 317, PNR Building, Sydney, NSW, Australia
4. School of Civil Engineering, Faculty of Engineering and IT, The University of Sydney, Room 415, PNR Building, Sydney, NSW, Australia - ISSN：1588-2861
文摘
Although co-authorship in scientific research has a long history the analysis of co-authorship network to explore scientific collaboration among authors is a relatively new research area. Studies of current literature about co-authorship networks mostly give emphasis to understand patterns of scientific collaborations, to capture collaborative statistics, and to propose valid and reliable measures for identifying prominent author(s). However, there is no such study in the literature which conducts a longitudinal analysis of co-authorship networks. Using a dataset that spans over 20?years, this paper attempts to explore efficiency and trend of co-authorship networks. Two scientists are considered connected if they have co-authored a paper, and these types of connections between two scientists eventually constitute co-authorship networks. Co-authorship networks evolve among researchers over time in specific research domains as well as in interdisciplinary research areas. Scientists from diverse research areas and different geographical locations may participate in one specific co-authorship network whereas an individual scientist may belong to different co-authorship networks. In this paper, we study a longitudinal co-authorship network of a specific scientific research area. By applying approaches to analyze longitudinal network data, in addition to known methods and measures of current co-authorship literature, we explore a co-authorship network of a relatively young and emerging research discipline to understand its trend of evolution pattern and proximity of efficiency.