Search (15 results, page 1 of 1)

0.021671817 = product of:
  0.043343633 = sum of:
    0.022971334 = weight(_text_:library in 4291) [ClassicSimilarity], result of:
      0.022971334 = score(doc=4291,freq=2.0), product of:
        0.1317883 = queryWeight, product of:
          2.6293786 = idf(docFreq=8668, maxDocs=44218)
          0.050121464 = queryNorm
        0.17430481 = fieldWeight in 4291, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.6293786 = idf(docFreq=8668, maxDocs=44218)
          0.046875 = fieldNorm(doc=4291)
    0.0203723 = product of:
      0.0407446 = sum of:
        0.0407446 = weight(_text_:22 in 4291) [ClassicSimilarity], result of:
          0.0407446 = score(doc=4291,freq=2.0), product of:
            0.17551683 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.050121464 = queryNorm
            0.23214069 = fieldWeight in 4291, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.046875 = fieldNorm(doc=4291)
      0.5 = coord(1/2)
  0.5 = coord(2/4)

Abstract

Counts of tweets and Mendeley user libraries have been proposed as altmetric alternatives to citation counts for the impact assessment of articles. Although both have been investigated to discover whether they correlate with article citations, it is not known whether users tend to tweet or save (in Mendeley) the same kinds of articles that they cite. In response, this article compares pairs of articles that are tweeted, saved to a Mendeley library, or cited by the same user, but possibly a different user for each source. The study analyzes 1,131,318 articles published in 2012, with minimum tweeted (10), saved to Mendeley (100), and cited (10) thresholds. The results show surprisingly minor overall overlaps between the three phenomena. The importance of journals for Twitter and the presence of many bots at different levels of activity suggest that this site has little value for impact altmetrics. The moderate differences between patterns of saving and citation suggest that Mendeley can be used for some types of impact assessments, but sensitivity is needed for underlying differences.

Date

28. 7.2018 10:00:22

0.01805985 = product of:
  0.0361197 = sum of:
    0.01914278 = weight(_text_:library in 57) [ClassicSimilarity], result of:
      0.01914278 = score(doc=57,freq=2.0), product of:
        0.1317883 = queryWeight, product of:
          2.6293786 = idf(docFreq=8668, maxDocs=44218)
          0.050121464 = queryNorm
        0.14525402 = fieldWeight in 57, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.6293786 = idf(docFreq=8668, maxDocs=44218)
          0.0390625 = fieldNorm(doc=57)
    0.016976917 = product of:
      0.033953834 = sum of:
        0.033953834 = weight(_text_:22 in 57) [ClassicSimilarity], result of:
          0.033953834 = score(doc=57,freq=2.0), product of:
            0.17551683 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.050121464 = queryNorm
            0.19345059 = fieldWeight in 57, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0390625 = fieldNorm(doc=57)
      0.5 = coord(1/2)
  0.5 = coord(2/4)

Abstract

Webometric network analyses have been used to map the connectivity of groups of websites to identify clusters, important sites or overall structure. Such analyses have mainly been based upon hyperlink counts, the number of hyperlinks between a pair of websites, although some have used title mentions or URL citations instead. The ability to automatically gather hyperlink counts from Yahoo! ceased in April 2011 and the ability to manually gather such counts was due to cease by early 2012, creating a need for alternatives. This article assesses URL citations and title mentions as possible replacements for hyperlinks in both binary and weighted direct link and co-inlink network diagrams. It also assesses three different types of data for the network connections: hit count estimates, counts of matching URLs, and filtered counts of matching URLs. Results from analyses of U.S. library and information science departments and U.K. universities give evidence that metrics based upon URLs or titles can be appropriate replacements for metrics based upon hyperlinks for both binary and weighted networks, although filtered counts of matching URLs are necessary to give the best results for co-title mention and co-URL citation network diagrams.

Date

6. 4.2012 18:16:22

0.010770457 = product of:
  0.043081827 = sum of:
    0.043081827 = weight(_text_:digital in 3966) [ClassicSimilarity], result of:
      0.043081827 = score(doc=3966,freq=2.0), product of:
        0.19770671 = queryWeight, product of:
          3.944552 = idf(docFreq=2326, maxDocs=44218)
          0.050121464 = queryNorm
        0.21790776 = fieldWeight in 3966, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.944552 = idf(docFreq=2326, maxDocs=44218)
          0.0390625 = fieldNorm(doc=3966)
  0.25 = coord(1/4)

Abstract

The web contains a huge number of digital pictures. For scholars publishing such images it is important to know how well used their images are, but no method seems to have been developed for monitoring the value of academic images. In particular, can the impact of scientific or artistic images be assessed through identifying images copied or reused on the Internet? This article explores a case study of 260 NASA images to investigate whether the TinEye search engine could theoretically help to provide this information. The results show that the selected pictures had a median of 11 online copies each. However, a classification of 210 of these copies reveals that only 1.4% were explicitly used in academic publications, reflecting research impact, and the majority of the NASA pictures were used for informal scholarly (or educational) communication (37%). Additional analyses of world famous paintings and scientific images about pathology and molecular structures suggest that image contents are important for the type and extent of image use. Although it is reasonable to use statistics derived from TinEye for assessing image reuse value, the extent of its image indexing is not known.

0.0057428335 = product of:
  0.022971334 = sum of:
    0.022971334 = weight(_text_:library in 2495) [ClassicSimilarity], result of:
      0.022971334 = score(doc=2495,freq=2.0), product of:
        0.1317883 = queryWeight, product of:
          2.6293786 = idf(docFreq=8668, maxDocs=44218)
          0.050121464 = queryNorm
        0.17430481 = fieldWeight in 2495, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.6293786 = idf(docFreq=8668, maxDocs=44218)
          0.046875 = fieldNorm(doc=2495)
  0.25 = coord(1/4)

Abstract

In theory, articles can attract readers on the social reference sharing site Mendeley before they can attract citations, so Mendeley altmetrics could provide early indications of article impact. This article investigates the influence of time on the number of Mendeley readers of an article through a theoretical discussion and an investigation into the relationship between counts of readers of, and citations to, 4 general library and information science (LIS) journals. For this discipline, it takes about 7 years for articles to attract as many Scopus citations as Mendeley readers, and after this the Spearman correlation between readers and citers is stable at about 0.6 for all years. This suggests that Mendeley readership counts may be useful impact indicators for both newer and older articles. The lack of dates for individual Mendeley article readers and an unknown bias toward more recent articles mean that readership data should be normalized individually by year, however, before making any comparisons between articles published in different years.

0.005093075 = product of:
  0.0203723 = sum of:
    0.0203723 = product of:
      0.0407446 = sum of:
        0.0407446 = weight(_text_:22 in 4345) [ClassicSimilarity], result of:
          0.0407446 = score(doc=4345,freq=2.0), product of:
            0.17551683 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.050121464 = queryNorm
            0.23214069 = fieldWeight in 4345, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.046875 = fieldNorm(doc=4345)
      0.5 = coord(1/2)
  0.25 = coord(1/4)

Date

22. 1.2011 14:27:06

0.005093075 = product of:
  0.0203723 = sum of:
    0.0203723 = product of:
      0.0407446 = sum of:
        0.0407446 = weight(_text_:22 in 2856) [ClassicSimilarity], result of:
          0.0407446 = score(doc=2856,freq=2.0), product of:
            0.17551683 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.050121464 = queryNorm
            0.23214069 = fieldWeight in 2856, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.046875 = fieldNorm(doc=2856)
      0.5 = coord(1/2)
  0.25 = coord(1/4)

Date

19. 3.2016 12:22:00

0.005093075 = product of:
  0.0203723 = sum of:
    0.0203723 = product of:
      0.0407446 = sum of:
        0.0407446 = weight(_text_:22 in 3211) [ClassicSimilarity], result of:
          0.0407446 = score(doc=3211,freq=2.0), product of:
            0.17551683 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.050121464 = queryNorm
            0.23214069 = fieldWeight in 3211, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.046875 = fieldNorm(doc=3211)
      0.5 = coord(1/2)
  0.25 = coord(1/4)

Date

16.11.2016 11:07:22

0.004785695 = product of:
  0.01914278 = sum of:
    0.01914278 = weight(_text_:library in 4465) [ClassicSimilarity], result of:
      0.01914278 = score(doc=4465,freq=2.0), product of:
        0.1317883 = queryWeight, product of:
          2.6293786 = idf(docFreq=8668, maxDocs=44218)
          0.050121464 = queryNorm
        0.14525402 = fieldWeight in 4465, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.6293786 = idf(docFreq=8668, maxDocs=44218)
          0.0390625 = fieldNorm(doc=4465)
  0.25 = coord(1/4)

Abstract

Increasing interdisciplinarity has been a policy objective since the 1990s, promoted by many governments and funding agencies, but the question is: How deeply has this affected the social sciences? Although numerous articles have suggested that research has become more interdisciplinary, yet no study has compared the extent to which the interdisciplinarity of different social science subjects has changed. To address this gap, changes in the level of interdisciplinarity since 1980 are investigated for subjects with many articles in the Social Sciences Citation Index (SSCI), using the percentage of cross-disciplinary citing documents (PCDCD) to evaluate interdisciplinarity. For the 14 SSCI subjects investigated, the median level of interdisciplinarity, as measured using cross-disciplinary citations, declined from 1980 to 1990, but rose sharply between 1990 and 2000, confirming previous research. This increase was not fully matched by an increase in the percentage of articles that were assigned to more than one subject category. Nevertheless, although on average the social sciences have recently become more interdisciplinary, the extent of this change varies substantially from subject to subject. The SSCI subject with the largest increase in interdisciplinarity between 1990 and 2000 was Information Science & Library Science (IS&LS) but there is evidence that the level of interdisciplinarity of IS&LS increased less quickly during the first decade of this century.

0.004785695 = product of:
  0.01914278 = sum of:
    0.01914278 = weight(_text_:library in 4626) [ClassicSimilarity], result of:
      0.01914278 = score(doc=4626,freq=2.0), product of:
        0.1317883 = queryWeight, product of:
          2.6293786 = idf(docFreq=8668, maxDocs=44218)
          0.050121464 = queryNorm
        0.14525402 = fieldWeight in 4626, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.6293786 = idf(docFreq=8668, maxDocs=44218)
          0.0390625 = fieldNorm(doc=4626)
  0.25 = coord(1/4)

Abstract

The primary webometric method for estimating the online impact of an organization is to count links to its website. Link counts have been available from commercial search engines for over a decade but this was set to end by early 2012 and so a replacement is needed. This article compares link counts to two alternative methods: URL citations and organization title mentions. New variations of these methods are also introduced. The three methods are compared against each other using Yahoo!. Two of the three methods (URL citations and organization title mentions) are also compared against each other using Bing. Evidence from a case study of 131 UK universities and 49 US Library and Information Science (LIS) departments suggests that Bing's Hit Count Estimates (HCEs) for popular title searches are not useful for webometric research but that Yahoo!'s HCEs for all three types of search and Bing's URL citation HCEs seem to be consistent. For exact URL counts the results of all three methods in Yahoo! and both methods in Bing are also consistent. Four types of accuracy factors are also introduced and defined: search engine coverage, search engine retrieval variation, search engine retrieval anomalies, and query polysemy.

0.004785695 = product of:
  0.01914278 = sum of:
    0.01914278 = weight(_text_:library in 2897) [ClassicSimilarity], result of:
      0.01914278 = score(doc=2897,freq=2.0), product of:
        0.1317883 = queryWeight, product of:
          2.6293786 = idf(docFreq=8668, maxDocs=44218)
          0.050121464 = queryNorm
        0.14525402 = fieldWeight in 2897, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.6293786 = idf(docFreq=8668, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2897)
  0.25 = coord(1/4)

Abstract

Although Mendeley bookmarking counts appear to correlate moderately with conventional citation metrics, it is not known whether academic publications are bookmarked in Mendeley in order to be read or not. Without this information, it is not possible to give a confident interpretation of altmetrics derived from Mendeley. In response, a survey of 860 Mendeley users shows that it is reasonable to use Mendeley bookmarking counts as an indication of readership because most (55%) users with a Mendeley library had read or intended to read at least half of their bookmarked publications. This was true across all broad areas of scholarship except for the arts and humanities (42%). About 85% of the respondents also declared that they bookmarked articles in Mendeley to cite them in their publications, but some also bookmark articles for use in professional (50%), teaching (25%), and educational activities (13%). Of course, it is likely that most readers do not record articles in Mendeley and so these data do not represent all readers. In conclusion, Mendeley bookmark counts seem to be indicators of readership leading to a combination of scholarly impact and wider professional impact.

0.004785695 = product of:
  0.01914278 = sum of:
    0.01914278 = weight(_text_:library in 3766) [ClassicSimilarity], result of:
      0.01914278 = score(doc=3766,freq=2.0), product of:
        0.1317883 = queryWeight, product of:
          2.6293786 = idf(docFreq=8668, maxDocs=44218)
          0.050121464 = queryNorm
        0.14525402 = fieldWeight in 3766, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.6293786 = idf(docFreq=8668, maxDocs=44218)
          0.0390625 = fieldNorm(doc=3766)
  0.25 = coord(1/4)

Abstract

SlideShare is a free social website that aims to help users distribute and find presentations. Owned by LinkedIn since 2012, it targets a professional audience but may give value to scholarship through creating a long-term record of the content of talks. This article tests this hypothesis by analyzing sets of general and scholarly related SlideShare documents using content and citation analysis and popularity statistics reported on the site. The results suggest that academics, students, and teachers are a minority of SlideShare uploaders, especially since 2010, with most documents not being directly related to scholarship or teaching. About two thirds of uploaded SlideShare documents are presentation slides, with the remainder often being files associated with presentations or video recordings of talks. SlideShare is therefore a presentation-centered site with a predominantly professional user base. Although a minority of the uploaded SlideShare documents are cited by, or cite, academic publications, probably too few articles are cited by SlideShare to consider extracting SlideShare citations for research evaluation. Nevertheless, scholars should consider SlideShare to be a potential source of academic and nonacademic information, particularly in library and information science, education, and business.

0.004785695 = product of:
  0.01914278 = sum of:
    0.01914278 = weight(_text_:library in 4015) [ClassicSimilarity], result of:
      0.01914278 = score(doc=4015,freq=2.0), product of:
        0.1317883 = queryWeight, product of:
          2.6293786 = idf(docFreq=8668, maxDocs=44218)
          0.050121464 = queryNorm
        0.14525402 = fieldWeight in 4015, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.6293786 = idf(docFreq=8668, maxDocs=44218)
          0.0390625 = fieldNorm(doc=4015)
  0.25 = coord(1/4)

Abstract

Within science, citation counts are widely used to estimate research impact but publication delays mean that they are not useful for recent research. This gap can be filled by Mendeley reader counts, which are valuable early impact indicators for academic articles because they appear before citations and correlate strongly with them. Nevertheless, it is not known how Mendeley readership counts accumulate within the year of publication, and so it is unclear how soon they can be used. In response, this paper reports a longitudinal weekly study of the Mendeley readers of articles in 6 library and information science journals from 2016. The results suggest that Mendeley readers accrue from when articles are first available online and continue to steadily build. For journals with large publication delays, articles can already have substantial numbers of readers by their publication date. Thus, Mendeley reader counts may even be useful as early impact indicators for articles before they have been officially published in a journal issue. If field normalized indicators are needed, then these can be generated when journal issues are published using the online first date.

0.0042442293 = product of:
  0.016976917 = sum of:
    0.016976917 = product of:
      0.033953834 = sum of:
        0.033953834 = weight(_text_:22 in 4200) [ClassicSimilarity], result of:
          0.033953834 = score(doc=4200,freq=2.0), product of:
            0.17551683 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.050121464 = queryNorm
            0.19345059 = fieldWeight in 4200, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4200)
      0.5 = coord(1/2)
  0.25 = coord(1/4)

Date

22. 1.2011 14:29:23

0.0042442293 = product of:
  0.016976917 = sum of:
    0.016976917 = product of:
      0.033953834 = sum of:
        0.033953834 = weight(_text_:22 in 2593) [ClassicSimilarity], result of:
          0.033953834 = score(doc=2593,freq=2.0), product of:
            0.17551683 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.050121464 = queryNorm
            0.19345059 = fieldWeight in 2593, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2593)
      0.5 = coord(1/2)
  0.25 = coord(1/4)

Date

20. 1.2015 18:30:22

0.0042442293 = product of:
  0.016976917 = sum of:
    0.016976917 = product of:
      0.033953834 = sum of:
        0.033953834 = weight(_text_:22 in 3806) [ClassicSimilarity], result of:
          0.033953834 = score(doc=3806,freq=2.0), product of:
            0.17551683 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.050121464 = queryNorm
            0.19345059 = fieldWeight in 3806, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3806)
      0.5 = coord(1/2)
  0.25 = coord(1/4)

Date

20. 1.2015 18:30:22