Search (45 results, page 1 of 3)

  • × author_ss:"Ding, Y."
  1. Ding, Y.: Applying weighted PageRank to author citation networks (2011) 0.03 
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    Abstract
    This article aims to identify whether different weighted PageRank algorithms can be applied to author citation networks to measure the popularity and prestige of a scholar from a citation perspective. Information retrieval (IR) was selected as a test field and data from 1956-2008 were collected from Web of Science. Weighted PageRank with citation and publication as weighted vectors were calculated on author citation networks. The results indicate that both popularity rank and prestige rank were highly correlated with the weighted PageRank. Principal component analysis was conducted to detect relationships among these different measures. For capturing prize winners within the IR field, prestige rank outperformed all the other measures
    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
    Type
    a
  2. Ding, Y.; Zhang, G.; Chambers, T.; Song, M.; Wang, X.; Zhai, C.: Content-based citation analysis : the next generation of citation analysis (2014) 0.02 
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    Abstract
    Traditional citation analysis has been widely applied to detect patterns of scientific collaboration, map the landscapes of scholarly disciplines, assess the impact of research outputs, and observe knowledge transfer across domains. It is, however, limited, as it assumes all citations are of similar value and weights each equally. Content-based citation analysis (CCA) addresses a citation's value by interpreting each one based on its context at both the syntactic and semantic levels. This paper provides a comprehensive overview of CAA research in terms of its theoretical foundations, methodical approaches, and example applications. In addition, we highlight how increased computational capabilities and publicly available full-text resources have opened this area of research to vast possibilities, which enable deeper citation analysis, more accurate citation prediction, and increased knowledge discovery.
    Date
    22. 8.2014 16:52:04
    Source
    Journal of the Association for Information Science and Technology. 65(2014) no.9, S.1820-1833
    Type
    a
  3. Ding, Y.; Foo, S.: Ontology research and development : part 1 - a review of ontology generation (2002) 0.01 
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    Source
    Journal of information science. 28(2002) no.2, S.123-136
    Type
    a
  4. Ding, Y.: ¬A review of ontologies with the Semantic Web in view (2001) 0.01 
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    Source
    Journal of information science. 27(2001) no.?, S.377-384
    Type
    a
  5. Ding, Y.; Chowdhury, G.C.; Foo, S.: Bibliometric cartography of information retrieval research by using co-word analysis (2001) 0.01 
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    Source
    Information processing and management. 37(2001) no.6, S.817-842
    Type
    a
  6. Ding, Y.; Chowdhury, G.C.; Foo, S.: Incorporating the results of co-word analyses to increase search variety for information retrieval (2000) 0.01 
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    Source
    Journal of information science. 26(2000) no.6, S.429-451
    Type
    a
  7. Ding, Y.; Foo, S.: Ontology research and development : part 2 - a review of ontology mapping and evolving (2002) 0.01 
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    Source
    Journal of information science. 28(2002) no.3, S.375-388
    Type
    a
  8. Ding, Y.; Chowdhury, G.; Foo, S.: Organsising keywords in a Web search environment : a methodology based on co-word analysis (2000) 0.01 
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    Abstract
    The rapid development of the Internet and World Wide Web has caused some critical problem for information retrieval. Researchers have made several attempts to solve these problems. Thesauri and subject heading lists as traditional information retrieval tools have been criticised for their efficiency to tackle these newly emerging problems. This paper proposes an information retrieval tool generated by cocitation analysis, comprising keyword clusters with relationships based on the co-occurrences of keywords in the literature. Such a tool can play the role of an associative thesaurus that can provide information about the keywords in a domain that might be useful for information searching and query expansion
    Type
    a
  9. He, B.; Ding, Y.; Ni, C.: Mining enriched contextual information of scientific collaboration : a meso perspective (2011) 0.01 
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    Abstract
    Studying scientific collaboration using coauthorship networks has attracted much attention in recent years. How and in what context two authors collaborate remain among the major questions. Previous studies, however, have focused on either exploring the global topology of coauthorship networks (macro perspective) or ranking the impact of individual authors (micro perspective). Neither of them has provided information on the context of the collaboration between two specific authors, which may potentially imply rich socioeconomic, disciplinary, and institutional information on collaboration. Different from the macro perspective and micro perspective, this article proposes a novel method (meso perspective) to analyze scientific collaboration, in which a contextual subgraph is extracted as the unit of analysis. A contextual subgraph is defined as a small subgraph of a large-scale coauthorship network that captures relationship and context between two coauthors. This method is applied to the field of library and information science. Topological properties of all the subgraphs in four time spans are investigated, including size, average degree, clustering coefficient, and network centralization. Results show that contextual subgprahs capture useful contextual information on two authors' collaboration.
    Source
    Journal of the American Society for Information Science and Technology. 62(2011) no.5, S.831-845
    Type
    a
  10. Milojevic, S.; Sugimoto, C.R.; Yan, E.; Ding, Y.: ¬The cognitive structure of Library and Information Science : analysis of article title words (2011) 0.01 
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    Abstract
    This study comprises a suite of analyses of words in article titles in order to reveal the cognitive structure of Library and Information Science (LIS). The use of title words to elucidate the cognitive structure of LIS has been relatively neglected. The present study addresses this gap by performing (a) co-word analysis and hierarchical clustering, (b) multidimensional scaling, and (c) determination of trends in usage of terms. The study is based on 10,344 articles published between 1988 and 2007 in 16 LIS journals. Methodologically, novel aspects of this study are: (a) its large scale, (b) removal of non-specific title words based on the "word concentration" measure (c) identification of the most frequent terms that include both single words and phrases, and (d) presentation of the relative frequencies of terms using "heatmaps". Conceptually, our analysis reveals that LIS consists of three main branches: the traditionally recognized library-related and information-related branches, plus an equally distinct bibliometrics/scientometrics branch. The three branches focus on: libraries, information, and science, respectively. In addition, our study identifies substructures within each branch. We also tentatively identify "information seeking behavior" as a branch that is establishing itself separate from the three main branches. Furthermore, we find that cognitive concepts in LIS evolve continuously, with no stasis since 1992. The most rapid development occurred between 1998 and 2001, influenced by the increased focus on the Internet. The change in the cognitive landscape is found to be driven by the emergence of new information technologies, and the retirement of old ones.
    Source
    Journal of the American Society for Information Science and Technology. 62(2011) no.10, S.1933-1953
    Type
    a
  11. Ding, Y.: Visualization of intellectual structure in information retrieval : author cocitation analysis (1998) 0.01 
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    Abstract
    Reports results of a cocitation analysis study from the international retrieval research field from 1987 to 1997. Data was taken from Social SciSearch, via Dialog, and the top 40 authors were submitted to author cocitation analysis to yield the intellectual structure of information retrieval. The resulting multidimensional scaling map revealed: identifiable author groups for information retrieval; location of these groups with respect to each other; extend of centrality and peripherality of authors within groups, proximities of authors within groups and across group boundaries; and the meaning of the axes of the map. Factor analysis was used to reveal the extent of the authors' research areas and statistical routines included: ALSCAL; clustering analysis and factor analysis
    Source
    International forum on information and documentation. 23(1998) no.1, S.25-36
    Type
    a
  12. Ding, Y.: Topic-based PageRank on author cocitation networks (2011) 0.01 
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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
    Type
    a
  13. Yan, E.; Ding, Y.: Applying centrality measures to impact analysis : a coauthorship network analysis (2009) 0.01 
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    Abstract
    Many studies on coauthorship networks focus on network topology and network statistical mechanics. This article takes a different approach by studying micro-level network properties with the aim of applying centrality measures to impact analysis. Using coauthorship data from 16 journals in the field of library and information science (LIS) with a time span of 20 years (1988-2007), we construct an evolving coauthorship network and calculate four centrality measures (closeness centrality, betweenness centrality, degree centrality, and PageRank) for authors in this network. We find that the four centrality measures are significantly correlated with citation counts. We also discuss the usability of centrality measures in author ranking and suggest that centrality measures can be useful indicators for impact analysis.
    Source
    Journal of the American Society for Information Science and Technology. 60(2009) no.10, S.2107-2118
    Type
    a
  14. Yan, E.; Ding, Y.: Discovering author impact : a PageRank perspective (2011) 0.01 
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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
    Type
    a
  15. Yan, E.; Ding, Y.: Weighted citation : an indicator of an article's prestige (2010) 0.01 
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    Abstract
    The authors propose using the technique of weighted citation to measure an article's prestige. The technique allocates a different weight to each reference by taking into account the impact of citing journals and citation time intervals. Weightedcitation captures prestige, whereas citation counts capture popularity. They compare the value variances for popularity and prestige for articles published in the Journal of the American Society for Information Science and Technology from 1998 to 2007, and find that the majority have comparable status.
    Source
    Journal of the American Society for Information Science and Technology. 61(2010) no.8, S.1635-1643
    Type
    a
  16. Zhang, G.; Ding, Y.; Milojevic, S.: Citation content analysis (CCA) : a framework for syntactic and semantic analysis of citation content (2013) 0.01 
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    Abstract
    This study proposes a new framework for citation content analysis (CCA), for syntactic and semantic analysis of citation content that can be used to better analyze the rich sociocultural context of research behavior. This framework could be considered the next generation of citation analysis. The authors briefly review the history and features of content analysis in traditional social sciences and its previous application in library and information science (LIS). Based on critical discussion of the theoretical necessity of a new method as well as the limits of citation analysis, the nature and purposes of CCA are discussed, and potential procedures to conduct CCA, including principles to identify the reference scope, a two-dimensional (citing and cited) and two-module (syntactic and semantic) codebook, are provided and described. Future work and implications are also suggested.
    Source
    Journal of the American Society for Information Science and Technology. 64(2013) no.7, S.1490-1503
    Type
    a
  17. Sugimoto, C.R.; Li, D.; Russell, T.G.; Finlay, S.C.; Ding, Y.: ¬The shifting sands of disciplinary development : analyzing North American Library and Information Science dissertations using latent Dirichlet allocation (2011) 0.01 
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    Abstract
    This work identifies changes in dominant topics in library and information science (LIS) over time, by analyzing the 3,121 doctoral dissertations completed between 1930 and 2009 at North American Library and Information Science programs. The authors utilize latent Dirichlet allocation (LDA) to identify latent topics diachronically and to identify representative dissertations of those topics. The findings indicate that the main topics in LIS have changed substantially from those in the initial period (1930-1969) to the present (2000-2009). However, some themes occurred in multiple periods, representing core areas of the field: library history occurred in the first two periods; citation analysis in the second and third periods; and information-seeking behavior in the fourth and last period. Two topics occurred in three of the five periods: information retrieval and information use. One of the notable changes in the topics was the diminishing use of the word library (and related terms). This has implications for the provision of doctoral education in LIS. This work is compared to other earlier analyses and provides validation for the use of LDA in topic analysis of a discipline.
    Source
    Journal of the American Society for Information Science and Technology. 62(2011) no.1, S.185-204
    Type
    a
  18. Li, D.; Wang, Y.; Madden, A.; Ding, Y.; Sun, G.G.; Zhang, N.; Zhou, E.: Analyzing stock market trends using social media user moods and social influence (2019) 0.01 
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    Abstract
    Information from microblogs is gaining increasing attention from researchers interested in analyzing fluctuations in stock markets. Behavioral financial theory draws on social psychology to explain some of the irrational behaviors associated with financial decisions to help explain some of the fluctuations. In this study we argue that social media users who demonstrate an interest in finance can offer insights into ways in which irrational behaviors may affect a stock market. To test this, we analyzed all the data collected over a 3-month period in 2011 from Tencent Weibo (one of the largest microblogging websites in China). We designed a social influence (SI)-based Tencent finance-related moods model to simulate investors' irrational behaviors, and designed a Tencent Moods-based Stock Trend Analysis (TM_STA) model to detect correlations between Tencent moods and the Hushen-300 index (one of the most important financial indexes in China). Experimental results show that the proposed method can help explain the data fluctuation. The findings support the existing behavioral financial theory, and can help to understand short-term rises and falls in a stock market. We use behavioral financial theory to further explain our findings, and to propose a trading model to verify the proposed model.
    Source
    Journal of the Association for Information Science and Technology. 70(2019) no.9, S.1000-1013
    Type
    a
  19. Yan, E.; Ding, Y.; Sugimoto, C.R.: P-Rank: an indicator measuring prestige in heterogeneous scholarly networks (2011) 0.01 
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    Abstract
    Ranking scientific productivity and prestige are often limited to homogeneous networks. These networks are unable to account for the multiple factors that constitute the scholarly communication and reward system. This study proposes a new informetric indicator, P-Rank, for measuring prestige in heterogeneous scholarly networks containing articles, authors, and journals. P-Rank differentiates the weight of each citation based on its citing papers, citing journals, and citing authors. Articles from 16 representative library and information science journals are selected as the dataset. Principle Component Analysis is conducted to examine the relationship between P-Rank and other bibliometric indicators. We also compare the correlation and rank variances between citation counts and P-Rank scores. This work provides a new approach to examining prestige in scholarly communication networks in a more comprehensive and nuanced way.
    Source
    Journal of the American Society for Information Science and Technology. 62(2011) no.3, S.467-477
    Type
    a
  20. Ni, C.; Shaw, D.; Lind, S.M.; Ding, Y.: Journal impact and proximity : an assessment using bibliographic features (2013) 0.01 
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    Abstract
    Journals in the Information Science & Library Science category of Journal Citation Reports (JCR) were compared using both bibliometric and bibliographic features. Data collected covered journal impact factor (JIF), number of issues per year, number of authors per article, longevity, editorial board membership, frequency of publication, number of databases indexing the journal, number of aggregators providing full-text access, country of publication, JCR categories, Dewey decimal classification, and journal statement of scope. Three features significantly correlated with JIF: number of editorial board members and number of JCR categories in which a journal is listed correlated positively; journal longevity correlated negatively with JIF. Coword analysis of journal descriptions provided a proximity clustering of journals, which differed considerably from the clusters based on editorial board membership. Finally, a multiple linear regression model was built to predict the JIF based on all the collected bibliographic features.
    Source
    Journal of the American Society for Information Science and Technology. 64(2013) no.4, S.802-817
    Type
    a

Authors

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  • b 1
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