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Ding, Y.: Applying weighted PageRank to author citation networks (2011)
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- Date
- 22. 1.2011 13:02:21
- Source
- Journal of the American Society for Information Science and Technology. 62(2011) no.2, S.236-245
-
Ding, Y.; Zhang, G.; Chambers, T.; Song, M.; Wang, X.; Zhai, C.: Content-based citation analysis : the next generation of citation analysis (2014)
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- Date
- 22. 8.2014 16:52:04
- Source
- Journal of the Association for Information Science and Technology. 65(2014) no.9, S.1820-1833
-
Ding, Y.; Yan, E.; Frazho, A.; Caverlee, J.: PageRank for ranking authors in co-citation networks (2009)
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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.
- Source
- Journal of the American Society for Information Science and Technology. 60(2009) no.11, S.2229-2243
-
Yan, E.; Ding, Y.: Discovering author impact : a PageRank perspective (2011)
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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.
- Source
- Information processing and management. 47(2011) no.1, S.125-134
-
Bu, Y.; Ding, Y.; Xu, J.; Liang, X.; Gao, G.; Zhao, Y.: Understanding success through the diversity of collaborators and the milestone of career (2018)
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- Abstract
- Scientific collaboration is vital to many fields, and it is common to see scholars seek out experienced researchers or experts in a domain with whom they can share knowledge, experience, and resources. To explore the diversity of research collaborations, this article performs a temporal analysis on the scientific careers of researchers in the field of computer science. Specifically, we analyze collaborators using 2 indicators: the research topic diversity, measured by the Author-Conference-Topic model and cosine, and the impact diversity, measured by the normalized standard deviation of h-indices. We find that the collaborators of high-impact researchers tend to study diverse research topics and have diverse h-indices. Moreover, by setting PhD graduation as an important milestone in researchers' careers, we examine several indicators related to scientific collaboration and their effects on a career. The results show that collaborating with authoritative authors plays an important role prior to a researcher's PhD graduation, but working with non-authoritative authors carries more weight after PhD graduation.
- Source
- Journal of the Association for Information Science and Technology. 69(2018) no.1, S.87-97
-
Ding, Y.: Topic-based PageRank on author cocitation networks (2011)
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- Abstract
- Ranking authors is vital for identifying a researcher's impact and standing within a scientific field. There are many different ranking methods (e.g., citations, publications, h-index, PageRank, and weighted PageRank), but most of them are topic-independent. This paper proposes topic-dependent ranks based on the combination of a topic model and a weighted PageRank algorithm. The author-conference-topic (ACT) model was used to extract topic distribution of individual authors. Two ways for combining the ACT model with the PageRank algorithm are proposed: simple combination (I_PR) or using a topic distribution as a weighted vector for PageRank (PR_t). Information retrieval was chosen as the test field and representative authors for different topics at different time phases were identified. Principal component analysis (PCA) was applied to analyze the ranking difference between I_PR and PR_t.
- Source
- Journal of the American Society for Information Science and Technology. 62(2011) no.3, S.449-466
-
Zhai, Y.; Ding, Y.; Zhang, H.: Innovation adoption : broadcasting versus virality (2021)
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- Source
- Journal of the Association for Information Science and Technology. 72(2021) no.4, S.403-416
-
Xu, H.; Bu, Y.; Liu, M.; Zhang, C.; Sun, M.; Zhang, Y.; Meyer, E.; Salas, E.; Ding, Y.: Team power dynamics and team impact : new perspectives on scientific collaboration using career age as a proxy for team power (2022)
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- Source
- Journal of the Association for Information Science and Technology. 73(2022) no.10, S.1489-1505
-
Ding, Y.; Foo, S.: Ontology research and development : part 1 - a review of ontology generation (2002)
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- Source
- Journal of information science. 28(2002) no.2, S.123-136
-
Ding, Y.; Chowdhury, G.C.; Foo, S.: Bibliometric cartography of information retrieval research by using co-word analysis (2001)
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- Source
- Information processing and management. 37(2001) no.6, S.817-842
-
Ding, Y.; Chowdhury, G.C.; Foo, S.: Incorporating the results of co-word analyses to increase search variety for information retrieval (2000)
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- Source
- Journal of information science. 26(2000) no.6, S.429-451
-
Ding, Y.; Foo, S.: Ontology research and development : part 2 - a review of ontology mapping and evolving (2002)
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- Source
- Journal of information science. 28(2002) no.3, S.375-388
-
Ding, Y.: ¬A review of ontologies with the Semantic Web in view (2001)
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- Source
- Journal of information science. 27(2001) no.?, S.377-384
-
Ding, Y.; Jacob, E.K.; Fried, M.; Toma, I.; Yan, E.; Foo, S.; Milojevicacute, S.: Upper tag ontology for integrating social tagging data (2010)
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- Source
- Journal of the American Society for Information Science and Technology. 61(2010) no.3, S.505-521
-
Ding, Y.: Scholarly communication and bibliometrics : Part 1: The scholarly communication model: literature review (1998)
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- Source
- International forum on information and documentation. 23(1998) no.2, S.20-29
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Ding, Y.; Chowdhury, G.; Foo, S.: Organsising keywords in a Web search environment : a methodology based on co-word analysis (2000)
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- Pages
- S.327-332
-
Ding, Y.; Jacob, E.K.; Zhang, Z.; Foo, S.; Yan, E.; George, N.L.; Guo, L.: Perspectives on social tagging (2009)
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- Source
- Journal of the American Society for Information Science and Technology. 60(2009) no.12, S.2388-2401
-
Zhang, G.; Ding, Y.; Milojevic, S.: Citation content analysis (CCA) : a framework for syntactic and semantic analysis of citation content (2013)
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