z-logo
open-access-imgOpen Access
PageRank for ranking authors in co‐citation networks
Author(s) -
Ding Ying,
Yan Erjia,
Frazho Arthur,
Caverlee James
Publication year - 2009
Publication title -
journal of the american society for information science and technology
Language(s) - English
Resource type - Journals
eISSN - 1532-2890
pISSN - 1532-2882
DOI - 10.1002/asi.21171
Subject(s) - pagerank , centrality , ranking (information retrieval) , citation , rank (graph theory) , computer science , information retrieval , index (typography) , key (lock) , data mining , statistics , mathematics , world wide web , combinatorics , computer security
This paper studies how varied damping factors in the PageRank algorithm influence the ranking of authors and proposes weighted PageRank algorithms. We selected the 108 most highly cited authors in the information retrieval (IR) area from the 1970s to 2008 to form the author co‐citation network. We calculated the ranks of these 108 authors based on PageRank with the damping factor ranging from 0.05 to 0.95. In order to test the relationship between different measures, we compared PageRank and weighted PageRank results with the citation ranking, h‐index, and centrality measures. We found that in our author co‐citation network, citation rank is highly correlated with PageRank with different damping factors and also with different weighted PageRank algorithms; citation rank and PageRank are not significantly correlated with centrality measures; and h‐index rank does not significantly correlate with centrality measures but does significantly correlate with other measures. The key factors that have impact on the PageRank of authors in the author co‐citation network are being co‐cited with important authors.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom