Search (7 results, page 1 of 1)

  • × author_ss:"Yan, E."
  • × theme_ss:"Informetrie"
  1. Yan, E.: Finding knowledge paths among scientific disciplines (2014) 0.01
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    Date
    26.10.2014 20:22:22
  2. Zhao, M.; Yan, E.; Li, K.: Data set mentions and citations : a content analysis of full-text publications (2018) 0.01
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  3. Yan, E.; Chen, Z.; Li, K.: Authors' status and the perceived quality of their work : measuring citation sentiment change in nobel articles (2020) 0.01
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  4. Wu, C.; Yan, E.; Zhu, Y.; Li, K.: Gender imbalance in the productivity of funded projects : a study of the outputs of National Institutes of Health R01 grants (2021) 0.01
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  5. Yan, E.; Li, K.: Which domains do open-access journals do best in? : a 5-year longitudinal study (2018) 0.01
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  6. Ding, Y.; Yan, E.; Frazho, A.; Caverlee, J.: PageRank for ranking authors in co-citation networks (2009) 0.00
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    Abstract
    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.
  7. Yan, E.; Ding, Y.: Discovering author impact : a PageRank perspective (2011) 0.00
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    Abstract
    This article provides an alternative perspective for measuring author impact by applying PageRank algorithm to a coauthorship network. A weighted PageRank algorithm considering citation and coauthorship network topology is proposed. We test this algorithm under different damping factors by evaluating author impact in the informetrics research community. In addition, we also compare this weighted PageRank with the h-index, citation, and program committee (PC) membership of the International Society for Scientometrics and Informetrics (ISSI) conferences. Findings show that this weighted PageRank algorithm provides reliable results in measuring author impact.