Search (4 results, page 1 of 1)

0.017623993 = product of:
  0.052871976 = sum of:
    0.052871976 = weight(_text_:based in 1036) [ClassicSimilarity], result of:
      0.052871976 = score(doc=1036,freq=6.0), product of:
        0.15283063 = queryWeight, product of:
          3.0129938 = idf(docFreq=5906, maxDocs=44218)
          0.050723847 = queryNorm
        0.34595144 = fieldWeight in 1036, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          3.0129938 = idf(docFreq=5906, maxDocs=44218)
          0.046875 = fieldNorm(doc=1036)
  0.33333334 = coord(1/3)

Abstract

Historically, co-citation models have been based only on bibliographic information. Full-text analysis offers the opportunity to significantly improve the quality of the signals upon which these co-citation models are based. In this work we study the effect of reference proximity on the accuracy of co-citation clusters. Using a corpus of 270,521 full text documents from 2007, we compare the results of traditional co-citation clustering using only the bibliographic information to results from co-citation clustering where proximity between reference pairs is factored into the pairwise relationships. We find that accounting for reference proximity from full text can increase the textual coherence (a measure of accuracy) of a co-citation cluster solution by up to 30% over the traditional approach based on bibliographic information.

0.010175217 = product of:
  0.03052565 = sum of:
    0.03052565 = weight(_text_:based in 1015) [ClassicSimilarity], result of:
      0.03052565 = score(doc=1015,freq=2.0), product of:
        0.15283063 = queryWeight, product of:
          3.0129938 = idf(docFreq=5906, maxDocs=44218)
          0.050723847 = queryNorm
        0.19973516 = fieldWeight in 1015, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.0129938 = idf(docFreq=5906, maxDocs=44218)
          0.046875 = fieldNorm(doc=1015)
  0.33333334 = coord(1/3)

Abstract

This article provides an overview of studies that have used citation analysis in the field of humanities in the period 1951 to 2010. The work is based on an exhaustive search in databases-particularly those in library and information science-and on citation chaining from papers on citation analysis. The results confirm that use of this technique in the humanities is limited, and although there was some growth in the 1970s and 1980s, it has stagnated in the past 2 decades. Most of the work has been done by research staff, but almost one third involves library staff, and 15% has been done by students. The study also showed that less than one fourth of the works used a citation database such as the Arts & Humanities Citation Index and that 21% of the works were in publications other than library and information science journals. The United States has the greatest output, and English is by far the most frequently used language, and 13.9% of the studies are in other languages.

0.010175217 = product of:
  0.03052565 = sum of:
    0.03052565 = weight(_text_:based in 5217) [ClassicSimilarity], result of:
      0.03052565 = score(doc=5217,freq=2.0), product of:
        0.15283063 = queryWeight, product of:
          3.0129938 = idf(docFreq=5906, maxDocs=44218)
          0.050723847 = queryNorm
        0.19973516 = fieldWeight in 5217, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.0129938 = idf(docFreq=5906, maxDocs=44218)
          0.046875 = fieldNorm(doc=5217)
  0.33333334 = coord(1/3)

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.

0.008479347 = product of:
  0.025438042 = sum of:
    0.025438042 = weight(_text_:based in 613) [ClassicSimilarity], result of:
      0.025438042 = score(doc=613,freq=2.0), product of:
        0.15283063 = queryWeight, product of:
          3.0129938 = idf(docFreq=5906, maxDocs=44218)
          0.050723847 = queryNorm
        0.16644597 = fieldWeight in 613, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.0129938 = idf(docFreq=5906, maxDocs=44218)
          0.0390625 = fieldNorm(doc=613)
  0.33333334 = coord(1/3)

Abstract

Previous analyses identified research on environmental tobacco smoke to be subject to strong fluctuations as measured by both quantitative and qualitative indicators. The evolution of search algorithms (based on the Web of Science and Web of Knowledge database platforms) was used to show the impact of errors of omission and commission in the outcomes of scientometric research. Optimization of the search algorithm led to the complete reassessment of previously published findings on the performance of environmental tobacco smoke research. Instead of strong continuous growth, the field of environmental tobacco smoke research was shown to experience stagnation or slow growth since mid-1990s when evaluated quantitatively. Qualitative analysis revealed steady but slow increase in the citation rate and decrease in uncitedness. Country analysis revealed the North-European countries as leaders in environmental tobacco smoke research (when the normalized results were evaluated both quantitatively and qualitatively), whereas the United States ranked first only when assessing the total number of papers produced. Scientometric research artifacts, including both errors of omission and commission, were shown to be capable of completely obscuring the real output of the chosen research field.