Search (276 results, page 1 of 14)

  • × theme_ss:"Citation indexing"
  1. Van der Veer Martens, B.; Goodrum, G.: ¬The diffusion of theories : a functional approach (2006) 0.01 
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    Abstract
    This comparative case study of the diffusion and nondiffusion over time of eight theories in the social sciences uses citation analysis, citation context analysis, content analysis, surveys of editorial review boards, and personal interviews with theorists to develop a model of the theory functions that facilitate theory diffusion throughout specific intellectual communities. Unlike previous work on the diffusion of theories as innovations, this theory functions model differs in several important respects from the findings of previous studies that employed Everett Rogers's classic typology of innovation characteristics that promote diffusion. The model is also presented as a contribution to a more integrated theory of citation.
    Date
    22. 7.2006 15:20:01
    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) 0.01 
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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
    Type
    a
  3. Nicolaisen, J.: Citation analysis (2007) 0.01 
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    Date
    13. 7.2008 19:53:22
    Type
    a
  4. Døsen, K.: One more reference on self-reference (1992) 0.01 
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    Date
    7. 2.2005 14:10:22
    Type
    a
  5. Van der Veer Martens, B.: Do citation systems represent theories of truth? (2001) 0.01 
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    Date
    22. 7.2006 15:22:28
    Type
    a
  6. Garfield, E.; Stock, W.G.: Citation Consciousness : Interview with Eugene Garfiels, chairman emeritus of ISI; Philadelphia (2002) 0.01 
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    Source
    Password. 2002, H.6, S.22-25
    Type
    a
  7. Garfield, E.: Recollections of Irving H. Sher 1924-1996 : Polymath/information scientist extraordinaire (2001) 0.01 
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    Abstract
    Over a 35-year period, Irving H. Sher played a critical role in the development and implementation of the Science Citation Index and other ISI products. Trained as a biochemist, statistician, and linguist, Sher brought a unique combination of talents to ISI as Director of Quality Control and Director of Research and Development. His talents as a teacher and mentor evoked loyalty. He was a particularly inventive but self-taught programmer. In addition to the SCI, Social Sciences Citation Index, and Arts and Humanities Citation Index,
    Date
    16.12.2001 14:01:22
    Type
    a
  8. Tay, A.: ¬The next generation discovery citation indexes : a review of the landscape in 2020 (2020) 0.01 
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    Abstract
    Conclusion There is a reason why Google Scholar and Web of Science/Scopus are kings of the hills in their various arenas. They have strong brand recogniton, a head start in development and a mass of eyeballs and users that leads to an almost virtious cycle of improvement. Competing against such well established competitors is not easy even when one has deep pockets (Microsoft) or a killer idea (scite). It will be interesting to see how the landscape will look like in 2030. Stay tuned for part II where I review each particular index.
    Date
    17.11.2020 12:22:59
    Type
    a
  9. Malanga, G.: Classifying and screening journal literature with citation data (1982) 0.01 
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  10. Fröhlich, G.: ¬Das Messen des leicht Meßbaren : Output-Indikatoren, Impact-Maße: Artefakte der Szeintometrie? (1999) 0.01 
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  11. Mingers, J.; Burrell, Q.L.: Modeling citation behavior in Management Science journals (2006) 0.01 
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    Abstract
    Citation rates are becoming increasingly important in judging the research quality of journals, institutions and departments, and individual faculty. This paper looks at the pattern of citations across different management science journals and over time. A stochastic model is proposed which views the generating mechanism of citations as a gamma mixture of Poisson processes generating overall a negative binomial distribution. This is tested empirically with a large sample of papers published in 1990 from six management science journals and found to fit well. The model is extended to include obsolescence, i.e., that the citation rate for a paper varies over its cited lifetime. This leads to the additional citations distribution which shows that future citations are a linear function of past citations with a time-dependent and decreasing slope. This is also verified empirically in a way that allows different obsolescence functions to be fitted to the data. Conclusions concerning the predictability of future citations, and future research in this area are discussed.
    Date
    26.12.2007 19:22:05
    Type
    a
  12. Bensman, S.J.: Eugene Garfield, Francis Narin, and PageRank : the theoretical bases of the Google search engine (2013) 0.01 
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    Abstract
    This paper presents a test of the validity of using Google Scholar to evaluate the publications of researchers by comparing the premises on which its search engine, PageRank, is based, to those of Garfield's theory of citation indexing. It finds that the premises are identical and that PageRank and Garfield's theory of citation indexing validate each other.
    Date
    17.12.2013 11:02:22
    Type
    a
  13. Thelwall, M.; Harries, G.: ¬The connection between the research of a university and counts of links to its Web pages : an investigation based upon a classification of the relationships of pages to the research of the host university (2003) 0.01 
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    Abstract
    Results from recent advances in link metrics have demonstrated that the hyperlink structure of national university systems can be strongly related to the research productivity of the individual institutions. This paper uses a page categorization to show that restricting the metrics to subsets more closely related to the research of the host university can produce even stronger associations. A partial overlap was also found between the effects of applying advanced document models and separating page types, but the best results were achieved through a combination of the two.
    Type
    a
  14. Kurtz, M.J.; Eichhorn, G.; Accomazzi, A.; Grant, C.; Demleitner, M.; Henneken, E.; Murray, S.S.: ¬The effect of use and access on citations (2005) 0.00 
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  15. Larivière, V.; Gingras, Y.; Archambault, E.: ¬The decline in the concentration of citations, 1900-2007 (2009) 0.00 
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    Date
    22. 3.2009 19:22:35
    Type
    a
  16. Ma, N.; Guan, J.; Zhao, Y.: Bringing PageRank to the citation analysis (2008) 0.00 
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    Abstract
    The paper attempts to provide an alternative method for measuring the importance of scientific papers based on the Google's PageRank. The method is a meaningful extension of the common integer counting of citations and is then experimented for bringing PageRank to the citation analysis in a large citation network. It offers a more integrated picture of the publications' influence in a specific field. We firstly calculate the PageRanks of scientific papers. The distributional characteristics and comparison with the traditionally used number of citations are then analyzed in detail. Furthermore, the PageRank is implemented in the evaluation of research influence for several countries in the field of Biochemistry and Molecular Biology during the time period of 2000-2005. Finally, some advantages of bringing PageRank to the citation analysis are concluded.
    Date
    31. 7.2008 14:22:05
    Type
    a
  17. Morris, S.A.; Yen, G.; Wu, Z.; Asnake, B.: Time line visualization of research fronts (2003) 0.00 
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    Abstract
    Research fronts, defined as clusters of documents that tend to cite a fixed, time invariant set of base documents, are plotted as time lines for visualization and exploration. Using a set of documents related to the subject of anthrax research, this article illustrates the construction, exploration, and interpretation of time lines for the purpose of identifying and visualizing temporal changes in research activity through journal articles. Such information is useful for presentation to meinbers of expert panels used for technology forecasting.
    Type
    a
  18. Zhang, G.; Ding, Y.; Milojevic, S.: Citation content analysis (CCA) : a framework for syntactic and semantic analysis of citation content (2013) 0.00 
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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.
    Type
    a
  19. Daquino, M.; Peroni, S.; Shotton, D.; Colavizza, G.; Ghavimi, B.; Lauscher, A.; Mayr, P.; Romanello, M.; Zumstein, P.: ¬The OpenCitations Data Model (2020) 0.00 
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    Abstract
    A variety of schemas and ontologies are currently used for the machine-readable description of bibliographic entities and citations. This diversity, and the reuse of the same ontology terms with different nuances, generates inconsistencies in data. Adoption of a single data model would facilitate data integration tasks regardless of the data supplier or context application. In this paper we present the OpenCitations Data Model (OCDM), a generic data model for describing bibliographic entities and citations, developed using Semantic Web technologies. We also evaluate the effective reusability of OCDM according to ontology evaluation practices, mention existing users of OCDM, and discuss the use and impact of OCDM in the wider open science community.
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    a
  20. Campanario, J.M.: Have referees rejected some of the most-cited articles of all times? (1996) 0.00 
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    Abstract
    In this article a quantitative study is reported on the resistance that scientists may encounter when they do innovative work or when they attempt to publish articles that later become highly cited. A set of 205 commentaries by authors of some of the most-cited papers of all times have been examined in order to identify those articles whose authors encountered difficulty in getting his or her work published. There are 22 commentaries (10,7%) in which authors mention some difficulty or resistance in doing or publishing the research reported in the article. Three of the articles which had problems in being published are the most cited from their respective journals. According the authors' commentaries, although sometimes referees' negative evaluations can help improve the articles, in other instances referees and editors wrongly rejected the highly cited articles
    Type
    a

Authors

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