Building and Analyzing a Global Co-Authorship Network Using Google Scholar Data-Reference-Cited by-同舟云学术

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Building and Analyzing a Global Co-Authorship Network Using Google Scholar Data

Published:2017 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 26th International Conference on World Wide Web Companion - WWW '17 Companion
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Author:

Chen Yang¹,Ding Cong²,Hu Jiyao¹,Chen Ruichuan³,Hui Pan⁴,Fu Xiaoming⁵

Affiliation:

1. Fudan University & Chinese Academy of Sciences, Shanghai, China

2. Cornell University, Ithaca, USA

3. Nokia Bell Labs, Stuttgart, Germany

4. The Hong Kong University of Science and Technology, Hong Kong, Hong Kong

5. University of Goettingen, Goettingen, Germany

Publisher

ACM Press

Reference17 articles.

1. Y.-Y. Ahn, S. Han, H. Kwak, Y.-H. Eom, S. Moon, and H. Jeong. Analysis of Topological Characteristics of Huge Online Social Networking Services. In Proc. of WWW, 2007.

2. C. Ding, Y. Chen, and X. Fu. Crowd Crawling: Towards Collaborative Data Collection for Large-scale Online Social Networks. In Proc. of ACM COSN, 2013.

3. L. Egghe. Theory and practise of the g-index. Scientometrics, 69(1):131--152, 2006.

4. B. Fonseca, R. B. Sampaio, M. V. d. A. Fonseca, and F. Zicker. Co-authorship network analysis in health research: method and potential use. Health Research Policy and Systems, 14(1):34, 2016.

5. M. Gjoka, M. Kurant, et al. Walking in Facebook: A case study of unbiased sampling of OSNs. In INFOCOM, 2010.

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