Search (5 results, page 1 of 1)

0.0026742492 = product of:
  0.0053484985 = sum of:
    0.0053484985 = product of:
      0.010696997 = sum of:
        0.010696997 = weight(_text_:a in 2499) [ClassicSimilarity], result of:
          0.010696997 = score(doc=2499,freq=20.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.20142901 = fieldWeight in 2499, product of:
              4.472136 = tf(freq=20.0), with freq of:
                20.0 = termFreq=20.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2499)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

This study introduces a new proposal to refine the classification of the SCImago Journal and Country Rank (SJR) platform by using clustering techniques and an alternative combination of citation measures from an initial 18,891 SJR journal network. Thus, a journal-journal matrix including simultaneously fractionalized values of direct citation, cocitation, and coupling was symmetrized by cosine similarity and later transformed into distances before performing clustering. The results provided a new cluster-based subject structure comprising 290 clusters that emerge by executing Ward's clustering in two phases and using a mixed labeling procedure based on tf-idf scores of the original SJR category tags and significant words extracted from journal titles. In total, 13,716 SJR journals were classified using this new cluster-based scheme. Although more than 5,000 journals were omitted in the classification process, the method produced a consistent classification with a balanced structure of coherent and well-defined clusters, a moderated multiassignment of journals, and a softer concentration of journals over clusters than in the original SJR categories. New subject disciplines such as "nanoscience and nanotechnology" or "social work" were also detected, providing evidence of good performance of our approach in refining the journal classification and updating the subject classification structure.

Type

a

0.0020506454 = product of:
  0.004101291 = sum of:
    0.004101291 = product of:
      0.008202582 = sum of:
        0.008202582 = weight(_text_:a in 3554) [ClassicSimilarity], result of:
          0.008202582 = score(doc=3554,freq=6.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.1544581 = fieldWeight in 3554, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0546875 = fieldNorm(doc=3554)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

There have been many attempts to evaluate Web spaces an the basis of the information that they provide, their form or functionality, or even the importance given to each of them by the Web itself. The indicators that have been developed for this purpose fall into two groups: those based an the study of a Web space's formal characteristics, and those related to its link structure. In this study we examine most of the webometric indicators that have been proposed in the literature together with others of our own design by applying them to a set of thematically related Web spaces and analyzing the relationships between the different indicators.

Type

a

0.0020296127 = product of:
  0.0040592253 = sum of:
    0.0040592253 = product of:
      0.008118451 = sum of:
        0.008118451 = weight(_text_:a in 618) [ClassicSimilarity], result of:
          0.008118451 = score(doc=618,freq=8.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.15287387 = fieldWeight in 618, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046875 = fieldNorm(doc=618)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

We analyze the benefits in terms of scientific impact deriving from international collaboration, examining both those for a country when it collaborates and also those for the other countries when they are collaborating with the former. The data show the more countries there are involved in the collaboration, the greater the gain in impact. Contrary to what we expected, the scientific impact of a country does not significantly influence the benefit it derives from collaboration, but does seem to positively influence the benefit obtained by the other countries collaborating with it. Although there was a weak correlation between these two classes of benefit, the countries with the highest impact were clear outliers from this correlation, tending to provide proportionally more benefit to their collaborating countries than they themselves obtained. Two surprising findings were the null benefit resulting from collaboration with Iran, and the small benefit resulting from collaboration with the United States despite its high impact.

Type

a

0.0016913437 = product of:
  0.0033826875 = sum of:
    0.0033826875 = product of:
      0.006765375 = sum of:
        0.006765375 = weight(_text_:a in 1814) [ClassicSimilarity], result of:
          0.006765375 = score(doc=1814,freq=8.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.12739488 = fieldWeight in 1814, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0390625 = fieldNorm(doc=1814)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Using Scopus data, we construct a global map of science based on aggregated journal-journal citations from 1996-2012 (N of journals?=?20,554). This base map enables users to overlay downloads from Scopus interactively. Using a single year (e.g., 2012), results can be compared with mappings based on the Journal Citation Reports at the Web of Science (N?=?10,936). The Scopus maps are more detailed at both the local and global levels because of their greater coverage, including, for example, the arts and humanities. The base maps can be interactively overlaid with journal distributions in sets downloaded from Scopus, for example, for the purpose of portfolio analysis. Rao-Stirling diversity can be used as a measure of interdisciplinarity in the sets under study. Maps at the global and the local level, however, can be very different because of the different levels of aggregation involved. Two journals, for example, can both belong to the humanities in the global map, but participate in different specialty structures locally. The base map and interactive tools are available online (with instructions) at http://www.leydesdorff.net/scopus_ovl.

Type

a

8.4567186E-4 = product of:
  0.0016913437 = sum of:
    0.0016913437 = product of:
      0.0033826875 = sum of:
        0.0033826875 = weight(_text_:a in 3090) [ClassicSimilarity], result of:
          0.0033826875 = score(doc=3090,freq=2.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.06369744 = fieldWeight in 3090, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3090)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Type

a