Search (5 results, page 1 of 1)

  • × author_ss:"Rousseau, R."
  • × theme_ss:"Citation indexing"
  1. Ahlgren, P.; Jarneving, B.; Rousseau, R.: Requirements for a cocitation similarity measure, with special reference to Pearson's correlation coefficient (2003) 0.02
    0.015505663 = product of:
      0.031011326 = sum of:
        0.031011326 = sum of:
          0.0060511357 = weight(_text_:a in 5171) [ClassicSimilarity], result of:
            0.0060511357 = score(doc=5171,freq=10.0), product of:
              0.053105544 = queryWeight, product of:
                1.153047 = idf(docFreq=37942, maxDocs=44218)
                0.046056706 = queryNorm
              0.11394546 = fieldWeight in 5171, product of:
                3.1622777 = tf(freq=10.0), with freq of:
                  10.0 = termFreq=10.0
                1.153047 = idf(docFreq=37942, maxDocs=44218)
                0.03125 = fieldNorm(doc=5171)
          0.02496019 = weight(_text_:22 in 5171) [ClassicSimilarity], result of:
            0.02496019 = score(doc=5171,freq=2.0), product of:
              0.16128273 = queryWeight, product of:
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.046056706 = queryNorm
              0.15476047 = fieldWeight in 5171, product of:
                1.4142135 = tf(freq=2.0), with freq of:
                  2.0 = termFreq=2.0
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.03125 = fieldNorm(doc=5171)
      0.5 = coord(1/2)
    
    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
    Type
    a
  2. Frandsen, T.F.; Rousseau, R.: Article impact calculated over arbitrary periods (2005) 0.00
    0.0026849252 = product of:
      0.0053698504 = sum of:
        0.0053698504 = product of:
          0.010739701 = sum of:
            0.010739701 = weight(_text_:a in 3264) [ClassicSimilarity], result of:
              0.010739701 = score(doc=3264,freq=14.0), product of:
                0.053105544 = queryWeight, product of:
                  1.153047 = idf(docFreq=37942, maxDocs=44218)
                  0.046056706 = queryNorm
                0.20223314 = fieldWeight in 3264, product of:
                  3.7416575 = tf(freq=14.0), with freq of:
                    14.0 = termFreq=14.0
                  1.153047 = idf(docFreq=37942, maxDocs=44218)
                  0.046875 = fieldNorm(doc=3264)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Abstract
    In this paper we address the various formulations of impact of articles, usually groups of articles as gauged by citations that these articles receive over a certain period of time. The journal impact factor, as published by ISI (Philadelphia, PA), is the best-known example of a formulation of impact of journals (considered as a set of articles) but many others have been defined in the literature. Impact factors have varying publication and citation periods and the chosen length of these periods enables, e.g., a distinction between synchronous and diachronous impact factors. It is shown how an impact factor for the general case can be defined. Two alternatives for a general impact factor are proposed, depending an whether different publication years are seen as a whole, and hence treating each one of them differently, or by operating with citation periods of identical length but allowing each publication period different starting points.
    Type
    a
  3. Rousseau, R.; Zuccala, A.: ¬A classification of author co-citations : definitions and search strategies (2004) 0.00
    0.0023919214 = product of:
      0.0047838427 = sum of:
        0.0047838427 = product of:
          0.009567685 = sum of:
            0.009567685 = weight(_text_:a in 2266) [ClassicSimilarity], result of:
              0.009567685 = score(doc=2266,freq=16.0), product of:
                0.053105544 = queryWeight, product of:
                  1.153047 = idf(docFreq=37942, maxDocs=44218)
                  0.046056706 = queryNorm
                0.18016359 = fieldWeight in 2266, product of:
                  4.0 = tf(freq=16.0), with freq of:
                    16.0 = termFreq=16.0
                  1.153047 = idf(docFreq=37942, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=2266)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Abstract
    The term author co-citation is defined and classified according to four distinct forms: the pure first-author co-citation, the pure author co-citation, the general author co-citation, and the special co-authorlco-citation. Each form can be used to obtain one count in an author co-citation study, based an a binary counting rule, which either recognizes the co-citedness of two authors in a given reference list (1) or does not (0). Most studies using author co-citations have relied solely an first-author cocitation counts as evidence of an author's oeuvre or body of work contributed to a research field. In this article, we argue that an author's contribution to a selected field of study should not be limited, but should be based an his/her complete list of publications, regardless of author ranking. We discuss the implications associated with using each co-citation form and show where simple first-author co-citations fit within our classification scheme. Examples are given to substantiate each author co-citation form defined in our classification, including a set of sample Dialog(TM) searches using references extracted from the SciSearch database.
    Type
    a
  4. Rousseau, R.: Timelines in citation research (2006) 0.00
    0.0023435948 = product of:
      0.0046871896 = sum of:
        0.0046871896 = product of:
          0.009374379 = sum of:
            0.009374379 = weight(_text_:a in 1746) [ClassicSimilarity], result of:
              0.009374379 = score(doc=1746,freq=6.0), product of:
                0.053105544 = queryWeight, product of:
                  1.153047 = idf(docFreq=37942, maxDocs=44218)
                  0.046056706 = queryNorm
                0.17652355 = fieldWeight in 1746, product of:
                  2.4494898 = tf(freq=6.0), with freq of:
                    6.0 = termFreq=6.0
                  1.153047 = idf(docFreq=37942, maxDocs=44218)
                  0.0625 = fieldNorm(doc=1746)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Abstract
    The timeline used in ISI's Journal Citation Reports (JCR; Thomson ISI, formerly the Institute for Scientific Information, Philadelphia, PA) for half-life calculations, is not a timeline for (average) cited age. These two timelines are shifted over half a year.
    Type
    a
  5. Hu, X.; Rousseau, R.: Do citation chimeras exist? : The case of under-cited influential articles suffering delayed recognition (2019) 0.00
    0.001757696 = product of:
      0.003515392 = sum of:
        0.003515392 = product of:
          0.007030784 = sum of:
            0.007030784 = weight(_text_:a in 5217) [ClassicSimilarity], result of:
              0.007030784 = score(doc=5217,freq=6.0), product of:
                0.053105544 = queryWeight, product of:
                  1.153047 = idf(docFreq=37942, maxDocs=44218)
                  0.046056706 = queryNorm
                0.13239266 = fieldWeight in 5217, product of:
                  2.4494898 = tf(freq=6.0), with freq of:
                    6.0 = termFreq=6.0
                  1.153047 = idf(docFreq=37942, maxDocs=44218)
                  0.046875 = fieldNorm(doc=5217)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    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.
    Type
    a