Search (71 results, page 1 of 4)

  • × theme_ss:"Citation indexing"
  1. Bensman, S.J.: Eugene Garfield, Francis Narin, and PageRank : the theoretical bases of the Google search engine (2013) 0.04 
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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
  2. Ding, Y.; Zhang, G.; Chambers, T.; Song, M.; Wang, X.; Zhai, C.: Content-based citation analysis : the next generation of citation analysis (2014) 0.03 
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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
  3. Tay, A.: ¬The next generation discovery citation indexes : a review of the landscape in 2020 (2020) 0.03 
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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
  4. Snyder, H.; Bonzi, S.: Patterns of self-citation across disciplines : 1980-1989 (1998) 0.03 
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    Abstract
    Reports results of a study to examine the patterns of self citation in 6 disciplines distributed among the physical and social sciences and humanities. Sample articles were examined to deermine the relative numbers and ages of self citations and citations to other in the bibliographies and to the exposure given to each type of citation in the text of the articles. significant differences were found in the number and age of citations between disciplines. Overall, 9% of all citations were self citations; 15% of physical sciences citations were self citations, as opposed to 6% in the social sciences and 3% in the humanities. Within disciplines, there was no significantly different amount of coverage between self citations and citations to others. Overall, it appears that a lack of substantive differences in self citation behaviour is consistent across disciplines
    Date
    22. 5.1999 19:33:24
  5. Ma, N.; Guan, J.; Zhao, Y.: Bringing PageRank to the citation analysis (2008) 0.03 
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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
  6. Ahlgren, P.; Jarneving, B.; Rousseau, R.: Requirements for a cocitation similarity measure, with special reference to Pearson's correlation coefficient (2003) 0.02 
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    Abstract
    Ahlgren, Jarneving, and. Rousseau review accepted procedures for author co-citation analysis first pointing out that since in the raw data matrix the row and column values are identical i,e, the co-citation count of two authors, there is no clear choice for diagonal values. They suggest the number of times an author has been co-cited with himself excluding self citation rather than the common treatment as zeros or as missing values. When the matrix is converted to a similarity matrix the normal procedure is to create a matrix of Pearson's r coefficients between data vectors. Ranking by r and by co-citation frequency and by intuition can easily yield three different orders. It would seem necessary that the adding of zeros to the matrix will not affect the value or the relative order of similarity measures but it is shown that this is not the case with Pearson's r. Using 913 bibliographic descriptions form the Web of Science of articles form JASIS and Scientometrics, authors names were extracted, edited and 12 information retrieval authors and 12 bibliometric authors each from the top 100 most cited were selected. Co-citation and r value (diagonal elements treated as missing) matrices were constructed, and then reconstructed in expanded form. Adding zeros can both change the r value and the ordering of the authors based upon that value. A chi-squared distance measure would not violate these requirements, nor would the cosine coefficient. It is also argued that co-citation data is ordinal data since there is no assurance of an absolute zero number of co-citations, and thus Pearson is not appropriate. The number of ties in co-citation data make the use of the Spearman rank order coefficient problematic.
    Date
    9. 7.2006 10:22:35
  7. Nicolaisen, J.: Citation analysis (2007) 0.02 
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    Date
    13. 7.2008 19:53:22
  8. Døsen, K.: One more reference on self-reference (1992) 0.02 
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    Date
    7. 2.2005 14:10:22
  9. Van der Veer Martens, B.: Do citation systems represent theories of truth? (2001) 0.02 
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    Date
    22. 7.2006 15:22:28
  10. Garfield, E.: Long-term vs. short-term journal impact : does it matter? (1998) 0.02 
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  11. 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
  12. Larivière, V.; Gingras, Y.; Archambault, E.: ¬The decline in the concentration of citations, 1900-2007 (2009) 0.01 
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    Date
    22. 3.2009 19:22:35
  13. Noruzi, A.: Google Scholar : the new generation of citation indexes (2005) 0.01 
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    Abstract
    Google Scholar (http://scholar.google.com) provides a new method of locating potentially relevant articles on a given subject by identifying subsequent articles that cite a previously published article. An important feature of Google Scholar is that researchers can use it to trace interconnections among authors citing articles on the same topic and to determine the frequency with which others cite a specific article, as it has a "cited by" feature. This study begins with an overview of how to use Google Scholar for citation analysis and identifies advanced search techniques not well documented by Google Scholar. This study also compares the citation counts provided by Web of Science and Google Scholar for articles in the field of "Webometrics." It makes several suggestions for improving Google Scholar. Finally, it concludes that Google Scholar provides a free alternative or complement to other citation indexes.
  14. Sen, B.K.; Pandalai, T.A.; Karanjai, A.: Ranking of scientists - a new approach (1998) 0.01 
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    Abstract
    A formula for the ranking of scientists based on diachronous citation counts is proposed. The paper generalises the fact that the citation generation potential (CGP) is not the same for all papers, it differs from paper to paper, and also to a certain extent depends on the subject domain of the papers. The method of ranking proposed in no way replaces peer review. It merely acts as an aid for peers to help them arrive at a better judgement.
  15. White, H.D.; Wellman, B.; Nazer, N.: Does Citation Reflect Social Structure? : Longitudinal Evidence From the "Globenet" Interdisciplinary Research Group (2004) 0.01 
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    Abstract
    Many authors have posited a social component in citation, the consensus being that the citers and citees often have interpersonal as well as intellectual ties. Evidence for this belief has been rather meager, however, in part because social networks researchers have lacked bibliometric data (e.g., pairwise citation counts from online databases), and citation analysts have lacked sociometric data (e.g., pairwise measures of acquaintanceship). In 1997 Nazer extensively measured personal relationships and communication behaviors in what we call "Globenet," an international group of 16 researchers from seven disciplines that was established in 1993 to study human development. Since Globenet's membership is known, it was possible during 2002 to obtain citation records for all members in databases of the Institute for Scientific Information. This permitted examination of how members cited each other (intercited) in journal articles over the past three decades and in a 1999 book to which they all contributed. It was also possible to explore links between the intercitation data and the social and communication data. Using network-analytic techniques, we look at the growth of intercitation over time, the extent to which it follows disciplinary or interdisciplinary lines, whether it covaries with degrees of acquaintanceship, whether it reflects Globenet's organizational structure, whether it is associated with particular in-group communication patterns, and whether it is related to the cocitation of Globenet members. Results show cocitation to be a powerful predictor of intercitation in the journal articles, while being an editor or co-author is an important predictor in the book. Intellectual ties based an shared content did better as predictors than content-neutral social ties like friendship. However, interciters in Globenet communicated more than did noninterciters.
  16. Garfield, E.: Recollections of Irving H. Sher 1924-1996 : Polymath/information scientist extraordinaire (2001) 0.01 
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    Date
    16.12.2001 14:01:22
  17. Van der Veer Martens, B.; Goodrum, G.: ¬The diffusion of theories : a functional approach (2006) 0.01 
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    Date
    22. 7.2006 15:20:01
  18. Rosenberg, V.: ¬An assessment of ISI's new Web of Science : ISI's services brings citiation indexing to new and advanced researchers (1998) 0.01 
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    Abstract
    Comments on the affinity of Web technology and citation indexes and reviews the ISI service, Web of Science. Although still requiring refinement, it multiplies the effectiveness of an already effective search tool
  19. Brody, T.; Harnad, S.; Carr, L.: Earlier Web usage statistics as predictors of later citation impact (2006) 0.01 
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    Abstract
    The use of citation counts to assess the impact of research articles is well established. However, the citation impact of an article can only be measured several years after it has been published. As research articles are increasingly accessed through the Web, the number of times an article is downloaded can be instantly recorded and counted. One would expect the number of times an article is read to be related both to the number of times it is cited and to how old the article is. The authors analyze how short-term Web usage impact predicts medium-term citation impact. The physics e-print archive-arXiv.org-is used to test this.
  20. Campanario, J.M.: Have referees rejected some of the most-cited articles of all times? (1996) 0.01 
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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

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