Search (10 results, page 1 of 1)

  • × author_ss:"Thelwall, M."
  • × theme_ss:"Informetrie"
  • × year_i:[2010 TO 2020}
  1. Thelwall, M.; Maflahi, N.: Are scholarly articles disproportionately read in their own country? : An analysis of mendeley readers (2015) 0.01
    0.013010402 = product of:
      0.026020804 = sum of:
        0.026020804 = product of:
          0.10408322 = sum of:
            0.10408322 = weight(_text_:authors in 1850) [ClassicSimilarity], result of:
              0.10408322 = score(doc=1850,freq=6.0), product of:
                0.23861247 = queryWeight, product of:
                  4.558814 = idf(docFreq=1258, maxDocs=44218)
                  0.05234091 = queryNorm
                0.43620193 = fieldWeight in 1850, product of:
                  2.4494898 = tf(freq=6.0), with freq of:
                    6.0 = termFreq=6.0
                  4.558814 = idf(docFreq=1258, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=1850)
          0.25 = coord(1/4)
      0.5 = coord(1/2)
    
    Abstract
    International collaboration tends to result in more highly cited research and, partly as a result of this, many research funding schemes are specifically international in scope. Nevertheless, it is not clear whether this citation advantage is the result of higher quality research or due to other factors, such as a larger audience for the publications. To test whether the apparent advantage of internationally collaborative research may be due to additional interest in articles from the countries of the authors, this article assesses the extent to which the national affiliations of the authors of articles affect the national affiliations of their Mendeley readers. Based on English-language Web of Science articles in 10 fields from science, medicine, social science, and the humanities, the results of statistical models comparing author and reader affiliations suggest that, in most fields, Mendeley users are disproportionately readers of articles authored from within their own country. In addition, there are several cases in which Mendeley users from certain countries tend to ignore articles from specific other countries, although it is not clear whether this reflects national biases or different national specialisms within a field. In conclusion, research funders should not incentivize international collaboration on the basis that it is, in general, higher quality because its higher impact may be primarily due to its larger audience. Moreover, authors should guard against national biases in their reading to select only the best and most relevant publications to inform their research.
  2. Didegah, F.; Thelwall, M.: Determinants of research citation impact in nanoscience and nanotechnology (2013) 0.01
    0.012747538 = product of:
      0.025495077 = sum of:
        0.025495077 = product of:
          0.101980306 = sum of:
            0.101980306 = weight(_text_:authors in 737) [ClassicSimilarity], result of:
              0.101980306 = score(doc=737,freq=4.0), product of:
                0.23861247 = queryWeight, product of:
                  4.558814 = idf(docFreq=1258, maxDocs=44218)
                  0.05234091 = queryNorm
                0.42738882 = fieldWeight in 737, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  4.558814 = idf(docFreq=1258, maxDocs=44218)
                  0.046875 = fieldNorm(doc=737)
          0.25 = coord(1/4)
      0.5 = coord(1/2)
    
    Abstract
    This study investigates a range of metrics available when a nanoscience and nanotechnology article is published to see which metrics correlate more with the number of citations to the article. It also introduces the degree of internationality of journals and references as new metrics for this purpose. The journal impact factor; the impact of references; the internationality of authors, journals, and references; and the number of authors, institutions, and references were all calculated for papers published in nanoscience and nanotechnology journals in the Web of Science from 2007 to 2009. Using a zero-inflated negative binomial regression model on the data set, the impact factor of the publishing journal and the citation impact of the cited references were found to be the most effective determinants of citation counts in all four time periods. In the entire 2007 to 2009 period, apart from journal internationality and author numbers and internationality, all other predictor variables had significant effects on citation counts.
  3. Thelwall, M.; Maflahi, N.: Guideline references and academic citations as evidence of the clinical value of health research (2016) 0.01
    0.010637206 = product of:
      0.021274412 = sum of:
        0.021274412 = product of:
          0.042548824 = sum of:
            0.042548824 = weight(_text_:22 in 2856) [ClassicSimilarity], result of:
              0.042548824 = score(doc=2856,freq=2.0), product of:
                0.18328895 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.05234091 = 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)
      0.5 = coord(1/2)
    
    Date
    19. 3.2016 12:22:00
  4. Thelwall, M.; Sud, P.: Mendeley readership counts : an investigation of temporal and disciplinary differences (2016) 0.01
    0.010637206 = product of:
      0.021274412 = sum of:
        0.021274412 = product of:
          0.042548824 = sum of:
            0.042548824 = weight(_text_:22 in 3211) [ClassicSimilarity], result of:
              0.042548824 = score(doc=3211,freq=2.0), product of:
                0.18328895 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.05234091 = 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)
      0.5 = coord(1/2)
    
    Date
    16.11.2016 11:07:22
  5. Didegah, F.; Thelwall, M.: Co-saved, co-tweeted, and co-cited networks (2018) 0.01
    0.010637206 = product of:
      0.021274412 = sum of:
        0.021274412 = product of:
          0.042548824 = sum of:
            0.042548824 = weight(_text_:22 in 4291) [ClassicSimilarity], result of:
              0.042548824 = score(doc=4291,freq=2.0), product of:
                0.18328895 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.05234091 = 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(1/2)
    
    Date
    28. 7.2018 10:00:22
  6. Thelwall, M.; Sud, P.; Wilkinson, D.: Link and co-inlink network diagrams with URL citations or title mentions (2012) 0.01
    0.0088643385 = product of:
      0.017728677 = sum of:
        0.017728677 = product of:
          0.035457354 = sum of:
            0.035457354 = weight(_text_:22 in 57) [ClassicSimilarity], result of:
              0.035457354 = score(doc=57,freq=2.0), product of:
                0.18328895 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.05234091 = 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(1/2)
    
    Date
    6. 4.2012 18:16:22
  7. Thelwall, M.: Are Mendeley reader counts high enough for research evaluations when articles are published? (2017) 0.01
    0.0088643385 = product of:
      0.017728677 = sum of:
        0.017728677 = product of:
          0.035457354 = sum of:
            0.035457354 = weight(_text_:22 in 3806) [ClassicSimilarity], result of:
              0.035457354 = score(doc=3806,freq=2.0), product of:
                0.18328895 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.05234091 = 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)
      0.5 = coord(1/2)
    
    Date
    20. 1.2015 18:30:22
  8. Abrizah, A.; Thelwall, M.: Can the impact of non-Western academic books be measured? : an investigation of Google Books and Google Scholar for Malaysia (2014) 0.01
    0.007511559 = product of:
      0.015023118 = sum of:
        0.015023118 = product of:
          0.06009247 = sum of:
            0.06009247 = weight(_text_:authors in 1548) [ClassicSimilarity], result of:
              0.06009247 = score(doc=1548,freq=2.0), product of:
                0.23861247 = queryWeight, product of:
                  4.558814 = idf(docFreq=1258, maxDocs=44218)
                  0.05234091 = queryNorm
                0.25184128 = fieldWeight in 1548, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  4.558814 = idf(docFreq=1258, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=1548)
          0.25 = coord(1/4)
      0.5 = coord(1/2)
    
    Abstract
    Citation indicators are increasingly used in book-based disciplines to support peer review in the evaluation of authors and to gauge the prestige of publishers. However, because global citation databases seem to offer weak coverage of books outside the West, it is not clear whether the influence of non-Western books can be assessed with citations. To investigate this, citations were extracted from Google Books and Google Scholar to 1,357 arts, humanities and social sciences (AHSS) books published by 5 university presses during 1961-2012 in 1 non-Western nation, Malaysia. A significant minority of the books (23% in Google Books and 37% in Google Scholar, 45% in total) had been cited, with a higher proportion cited if they were older or in English. The combination of Google Books and Google Scholar is therefore recommended, with some provisos, for non-Western countries seeking to differentiate between books with some impact and books with no impact, to identify the highly-cited works or to develop an indicator of academic publisher prestige.
  9. Mohammadi, E.; Thelwall, M.; Haustein, S.; Larivière, V.: Who reads research articles? : an altmetrics analysis of Mendeley user categories (2015) 0.01
    0.007511559 = product of:
      0.015023118 = sum of:
        0.015023118 = product of:
          0.06009247 = sum of:
            0.06009247 = weight(_text_:authors in 2162) [ClassicSimilarity], result of:
              0.06009247 = score(doc=2162,freq=2.0), product of:
                0.23861247 = queryWeight, product of:
                  4.558814 = idf(docFreq=1258, maxDocs=44218)
                  0.05234091 = queryNorm
                0.25184128 = fieldWeight in 2162, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  4.558814 = idf(docFreq=1258, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=2162)
          0.25 = coord(1/4)
      0.5 = coord(1/2)
    
    Abstract
    Little detailed information is known about who reads research articles and the contexts in which research articles are read. Using data about people who register in Mendeley as readers of articles, this article explores different types of users of Clinical Medicine, Engineering and Technology, Social Science, Physics, and Chemistry articles inside and outside academia. The majority of readers for all disciplines were PhD students, postgraduates, and postdocs but other types of academics were also represented. In addition, many Clinical Medicine articles were read by medical professionals. The highest correlations between citations and Mendeley readership counts were found for types of users who often authored academic articles, except for associate professors in some sub-disciplines. This suggests that Mendeley readership can reflect usage similar to traditional citation impact if the data are restricted to readers who are also authors without the delay of impact measured by citation counts. At the same time, Mendeley statistics can also reveal the hidden impact of some research articles, such as educational value for nonauthor users inside academia or the impact of research articles on practice for readers outside academia.
  10. Kousha, K.; Thelwall, M.; Abdoli, M.: Goodreads reviews to assess the wider impacts of books (2017) 0.01
    0.007511559 = product of:
      0.015023118 = sum of:
        0.015023118 = product of:
          0.06009247 = sum of:
            0.06009247 = weight(_text_:authors in 3768) [ClassicSimilarity], result of:
              0.06009247 = score(doc=3768,freq=2.0), product of:
                0.23861247 = queryWeight, product of:
                  4.558814 = idf(docFreq=1258, maxDocs=44218)
                  0.05234091 = queryNorm
                0.25184128 = fieldWeight in 3768, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  4.558814 = idf(docFreq=1258, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=3768)
          0.25 = coord(1/4)
      0.5 = coord(1/2)
    
    Abstract
    Although peer-review and citation counts are commonly used to help assess the scholarly impact of published research, informal reader feedback might also be exploited to help assess the wider impacts of books, such as their educational or cultural value. The social website Goodreads seems to be a reasonable source for this purpose because it includes a large number of book reviews and ratings by many users inside and outside of academia. To check this, Goodreads book metrics were compared with different book-based impact indicators for 15,928 academic books across broad fields. Goodreads engagements were numerous enough in the arts (85% of books had at least one), humanities (80%), and social sciences (67%) for use as a source of impact evidence. Low and moderate correlations between Goodreads book metrics and scholarly or non-scholarly indicators suggest that reader feedback in Goodreads reflects the many purposes of books rather than a single type of impact. Although Goodreads book metrics can be manipulated, they could be used guardedly by academics, authors, and publishers in evaluations.