Journal
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
Volume 419, Issue -, Pages 29-39Publisher
ELSEVIER
DOI: 10.1016/j.physa.2014.10.006
Keywords
Co-author network; PageRank; Effective distance; Erdos number
Categories
Funding
- National Natural Science Foundation of China [61174022]
- R&D Program of China [2012BAH07B01]
- National High Technology Research and Development Program of China (863 Program) [2013AA013801]
- Chongqing Natural Science Foundation [CSCT, 2010BA2003]
- Program for New Century Excellent Talents in University [NCET-08-0345]
- Southwest University [SWU110021]
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In this paper, we propose a new method to evaluate the importance of nodes in a given network. The proposed method is based on the PageRank algorithm. However, we have made necessary improvements to combine the importance of the node itself and that of its community status. First, we propose an improved method to better evaluate the real impact of a paper. The proposed method calibrates the real influence of a paper over time. Then we propose a scheme of evaluating the contribution of each author in a paper. We later develop a new method to combine the information of the author itself and the structure of the co-author network. We use the number of co-authorship to calculate the effective distance between two authors, and evaluate the strength of their influence to each other with the law of gravity. The strength of influence is used to build a new network of authors, which is a comprehensive topological representation of both the quality of the node and its role in network. Finally, we apply our method to the Erdos co-author community and AMiner Citation Network to identify the most influential authors. (C) 2014 Elsevier B.V. All rights reserved.
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