Search (279 results, page 1 of 14)

  • × theme_ss:"Citation indexing"
  1. Wainer, J.; Valle, E.: What happens to computer science research after it is published? : Tracking CS research lines (2013) 0.09 
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    Abstract
    Are computer science papers extended after they are published? We have surveyed 200 computer science publications, 100 journal articles, and 100 conference papers, using self-citations to identify potential and actual continuations. We are interested in determining the proportion of papers that do indeed continue, how and when the continuation takes place, and whether any distinctions are found between the journal and conference populations. Despite the implicit assumption of a research line behind each paper, manifest in the ubiquitous "future research" notes that close many of them, we find that more than 70% of the papers are never continued.
    Source
    Journal of the American Society for Information Science and Technology. 64(2013) no.6, S.1104-1111
    Type
    a
  2. Abt, H.A.; Garfield, E.: Is the relationship between numbers of references and paper lengths the same for all sciences? (2002) 0.08 
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    Abstract
    It has been shown in the physical sciences that a paper's length is related to its number of references in a linear manner. Abt and Garfield here look at the life and social sciences with the thought that if the relation holds the citation counts will provide a measure of relative importance across these disciplines. In the life sciences 200 research papers from 1999-2000 were scanned in each of 10 journals to produce counts of 1000 word normalized pages. In the social sciences an average of 70 research papers in nine journals were scanned for the two-year period. Papers of average length in the various sciences have the same average number of references within plus or minus 17%. A look at the 30 to 60 papers over the two years in 18 review journals indicates twice the references of research papers of the same length.
    Source
    Journal of the American Society for Information Science and technology. 53(2002) no.13, S.1106-1112
    Type
    a
  3. Hu, X.; Rousseau, R.: Do citation chimeras exist? : The case of under-cited influential articles suffering delayed recognition (2019) 0.08 
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    Abstract
    In this study we investigate if articles suffering delayed recognition can at the same time be under-cited influential articles. Theoretically these two types of articles are independent, in the sense that suffering delayed recognition depends on the number and time distribution of received citations, while being an under-cited influential article depends only partially on the number of received (first generation) citations, and much more on second and third citation generations. Among 49 articles suffering delayed recognition we found 13 that are also under-cited influential. Based on a thorough investigation of these special cases we found that so-called authoritative citers play an important role in uniting the two different document types into a special citation chimera. Our investigation contributes to the classification of publications.
    Source
    Journal of the Association for Information Science and Technology. 70(2019) no.5, S.499-508
    Type
    a
  4. Nicolaisen, J.: Citation analysis (2007) 0.07 
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    Date
    13. 7.2008 19:53:22
    Source
    Annual review of information science and technology. 41(2007), S.xxx-xxx
    Type
    a
  5. Hyland, K.: Self-citation and self-reference : credibility and promotion in academic publication (2003) 0.07 
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    Abstract
    Hyland examines self referencing practices by analyzing their textual uses in 240 randomly chosen research papers and 800 abstracts across 80 expert selected journals from 1997 and 1998 in eight disciplines, as a key to their author's assumptions as to their own role in the research process and to the practices of their disciplines. Scanned texts produced a corpus of nearly 1.5 million words which was searched using WordPilot for first person pronouns and all mentions of an author's previous work. There were 6,689 instances of self reference in the papers and 459 in the abstracts; on the average 28 cases per paper, 17% of which were self citations. There was one self mention in every two abstracts. Nearly 70% of self reference and mention occurred in humanities and social science papers, but biologists employed the most self citation overall and 12% of hard science citations were found to be self citations. Interviews indicated that self citation was deemed important in establishing authority by fitting oneself into the research framework. Self mention arises in four main contexts: stating the goal or the structure of the paper, explaining a procedure, stating results or a claim, and elaborating an argument.
    Source
    Journal of the American Society for Information Science and technology. 54(2003) no.3, S.251-259
    Type
    a
  6. Van der Veer Martens, B.: Do citation systems represent theories of truth? (2001) 0.06 
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    Date
    22. 7.2006 15:22:28
    Source
    Information Research. 6(2001), no.2
    Type
    a
  7. Garfield, E.: Recollections of Irving H. Sher 1924-1996 : Polymath/information scientist extraordinaire (2001) 0.04 
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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
    Source
    Journal of the American Society for Information Science and technology. 52(2001) no.14, S.1197-1202
    Type
    a
  8. Chan, H.C.; Kim, H.-W.; Tan, W.C.: Information systems citation patterns from International Conference on Information Systems articles (2006) 0.04 
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    Abstract
    Research patterns could enhance understanding of the Information Systems (IS) field. Citation analysis is the methodology commonly used to determine such research patterns. In this study, the citation methodology is applied to one of the top-ranked Information Systems conferences - International Conference on Information Systems (ICIS). Information is extracted from papers in the proceedings of ICIS 2000 to 2002. A total of 145 base articles and 4,226 citations are used. Research patterns are obtained using total citations, citations per journal or conference, and overlapping citations. We then provide the citation ranking of journals and conferences. We also examine the difference between the citation ranking in this study and the ranking of IS journals and IS conferences in other studies. Based on the comparison, we confirm that IS research is a multidisciplinary research area. We also identify the most cited papers and authors in the IS research area, and the organizations most active in producing papers in the top-rated IS conference. We discuss the findings and implications of the study.
    Date
    3. 1.2007 17:22:03
    Source
    Journal of the American Society for Information Science and Technology. 57(2006) no.9, S.1263-1274
    Type
    a
  9. Larivière, V.; Gingras, Y.; Archambault, E.: ¬The decline in the concentration of citations, 1900-2007 (2009) 0.04 
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    Date
    22. 3.2009 19:22:35
    Source
    Journal of the American Society for Information Science and Technology. 60(2009) no.4, S.858-862
    Type
    a
  10. Van der Veer Martens, B.; Goodrum, G.: ¬The diffusion of theories : a functional approach (2006) 0.04 
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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
    Source
    Journal of the American Society for Information Science and Technology. 57(2006) no.3, S.330-341
    Type
    a
  11. Døsen, K.: One more reference on self-reference (1992) 0.03 
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    Date
    7. 2.2005 14:10:22
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    a
  12. Mingers, J.; Burrell, Q.L.: Modeling citation behavior in Management Science journals (2006) 0.03 
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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
    Source
    Information processing and management. 42(2006) no.6, S.1451-1464
    Type
    a
  13. 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
    Source
    Information processing and management. 44(2008) no.2, S.800-810
    Type
    a
  14. Campanario, J.M.: Have referees rejected some of the most-cited articles of all times? (1996) 0.03 
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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
    Source
    Journal of the American Society for Information Science. 47(1996) no.4, S.302-310
    Type
    a
  15. 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
    Source
    Journal of information science. 24(1998) no.6, S.431-435
    Type
    a
  16. 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
    Source
    Journal of the Association for Information Science and Technology. 65(2014) no.9, S.1820-1833
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    a
  17. H-Index auch im Web of Science (2008) 0.03 
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    Content
    "Zur Kurzmitteilung "Latest enhancements in Scopus: ... h-Index incorporated in Scopus" in den letzten Online-Mitteilungen (Online-Mitteilungen 92, S.31) ist zu korrigieren, dass der h-Index sehr wohl bereits im Web of Science enthalten ist. Allerdings findet man/frau diese Information nicht in der "cited ref search", sondern neben der Trefferliste einer Quick Search, General Search oder einer Suche über den Author Finder in der rechten Navigationsleiste unter dem Titel "Citation Report". Der "Citation Report" bietet für die in der jeweiligen Trefferliste angezeigten Arbeiten: - Die Gesamtzahl der Zitierungen aller Arbeiten in der Trefferliste - Die mittlere Zitationshäufigkeit dieser Arbeiten - Die Anzahl der Zitierungen der einzelnen Arbeiten, aufgeschlüsselt nach Publikationsjahr der zitierenden Arbeiten - Die mittlere Zitationshäufigkeit dieser Arbeiten pro Jahr - Den h-Index (ein h-Index von x sagt aus, dass x Arbeiten der Trefferliste mehr als x-mal zitiert wurden; er ist gegenüber sehr hohen Zitierungen einzelner Arbeiten unempfindlicher als die mittlere Zitationshäufigkeit)."
    Date
    6. 4.2008 19:04:22
    Type
    a
  18. 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
    Source
    Journal of the American Society for Information Science and technology. 54(2003) no.6, S.549-568
    Type
    a
  19. Garfield, E.; Stock, W.G.: Citation Consciousness : Interview with Eugene Garfiels, chairman emeritus of ISI; Philadelphia (2002) 0.02 
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    Source
    Password. 2002, H.6, S.22-25
    Type
    a
  20. Tay, A.: ¬The next generation discovery citation indexes : a review of the landscape in 2020 (2020) 0.02 
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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

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