Search (324 results, page 1 of 17)

  • × theme_ss:"Informetrie"
  • × language_ss:"e"
  1. Kousha, K.; Thelwall, M.: How is science cited on the Web? : a classification of google unique Web citations (2007) 0.01
    0.008292217 = product of:
      0.037314974 = sum of:
        0.027355025 = product of:
          0.05471005 = sum of:
            0.05471005 = weight(_text_:web in 586) [ClassicSimilarity], result of:
              0.05471005 = score(doc=586,freq=20.0), product of:
                0.09596372 = queryWeight, product of:
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.02940506 = queryNorm
                0.5701118 = fieldWeight in 586, product of:
                  4.472136 = tf(freq=20.0), with freq of:
                    20.0 = termFreq=20.0
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=586)
          0.5 = coord(1/2)
        0.009959949 = product of:
          0.019919898 = sum of:
            0.019919898 = weight(_text_:22 in 586) [ClassicSimilarity], result of:
              0.019919898 = score(doc=586,freq=2.0), product of:
                0.10297151 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.02940506 = queryNorm
                0.19345059 = fieldWeight in 586, 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=586)
          0.5 = coord(1/2)
      0.22222222 = coord(2/9)
    
    Abstract
    Although the analysis of citations in the scholarly literature is now an established and relatively well understood part of information science, not enough is known about citations that can be found on the Web. In particular, are there new Web types, and if so, are these trivial or potentially useful for studying or evaluating research communication? We sought evidence based upon a sample of 1,577 Web citations of the URLs or titles of research articles in 64 open-access journals from biology, physics, chemistry, and computing. Only 25% represented intellectual impact, from references of Web documents (23%) and other informal scholarly sources (2%). Many of the Web/URL citations were created for general or subject-specific navigation (45%) or for self-publicity (22%). Additional analyses revealed significant disciplinary differences in the types of Google unique Web/URL citations as well as some characteristics of scientific open-access publishing on the Web. We conclude that the Web provides access to a new and different type of citation information, one that may therefore enable us to measure different aspects of research, and the research process in particular; but to obtain good information, the different types should be separated.
  2. Meho, L.I.; Rogers, Y.: Citation counting, citation ranking, and h-index of human-computer interaction researchers : a comparison of Scopus and Web of Science (2008) 0.01
    0.00729929 = product of:
      0.032846805 = sum of:
        0.022886856 = product of:
          0.04577371 = sum of:
            0.04577371 = weight(_text_:web in 2352) [ClassicSimilarity], result of:
              0.04577371 = score(doc=2352,freq=14.0), product of:
                0.09596372 = queryWeight, product of:
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.02940506 = queryNorm
                0.47698978 = fieldWeight in 2352, product of:
                  3.7416575 = tf(freq=14.0), with freq of:
                    14.0 = termFreq=14.0
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=2352)
          0.5 = coord(1/2)
        0.009959949 = product of:
          0.019919898 = sum of:
            0.019919898 = weight(_text_:22 in 2352) [ClassicSimilarity], result of:
              0.019919898 = score(doc=2352,freq=2.0), product of:
                0.10297151 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.02940506 = queryNorm
                0.19345059 = fieldWeight in 2352, 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=2352)
          0.5 = coord(1/2)
      0.22222222 = coord(2/9)
    
    Abstract
    This study examines the differences between Scopus and Web of Science in the citation counting, citation ranking, and h-index of 22 top human-computer interaction (HCI) researchers from EQUATOR - a large British Interdisciplinary Research Collaboration project. Results indicate that Scopus provides significantly more coverage of HCI literature than Web of Science, primarily due to coverage of relevant ACM and IEEE peer-reviewed conference proceedings. No significant differences exist between the two databases if citations in journals only are compared. Although broader coverage of the literature does not significantly alter the relative citation ranking of individual researchers, Scopus helps distinguish between the researchers in a more nuanced fashion than Web of Science in both citation counting and h-index. Scopus also generates significantly different maps of citation networks of individual scholars than those generated by Web of Science. The study also presents a comparison of h-index scores based on Google Scholar with those based on the union of Scopus and Web of Science. The study concludes that Scopus can be used as a sole data source for citation-based research and evaluation in HCI, especially when citations in conference proceedings are sought, and that researchers should manually calculate h scores instead of relying on system calculations.
    Object
    Web of Science
  3. Asubiaro, T.V.; Onaolapo, S.: ¬A comparative study of the coverage of African journals in Web of Science, Scopus, and CrossRef (2023) 0.01
    0.006922013 = product of:
      0.03114906 = sum of:
        0.02118911 = product of:
          0.04237822 = sum of:
            0.04237822 = weight(_text_:web in 992) [ClassicSimilarity], result of:
              0.04237822 = score(doc=992,freq=12.0), product of:
                0.09596372 = queryWeight, product of:
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.02940506 = queryNorm
                0.4416067 = fieldWeight in 992, product of:
                  3.4641016 = tf(freq=12.0), with freq of:
                    12.0 = termFreq=12.0
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=992)
          0.5 = coord(1/2)
        0.009959949 = product of:
          0.019919898 = sum of:
            0.019919898 = weight(_text_:22 in 992) [ClassicSimilarity], result of:
              0.019919898 = score(doc=992,freq=2.0), product of:
                0.10297151 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.02940506 = queryNorm
                0.19345059 = fieldWeight in 992, 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=992)
          0.5 = coord(1/2)
      0.22222222 = coord(2/9)
    
    Abstract
    This is the first study that evaluated the coverage of journals from Africa in Web of Science, Scopus, and CrossRef. A list of active journals published in each of the 55 African countries was compiled from Ulrich's periodicals directory and African Journals Online (AJOL) website. Journal master lists for Web of Science, Scopus, and CrossRef were searched for the African journals. A total of 2,229 unique active African journals were identified from Ulrich (N = 2,117, 95.0%) and AJOL (N = 243, 10.9%) after removing duplicates. The volume of African journals in Web of Science and Scopus databases is 7.4% (N = 166) and 7.8% (N = 174), respectively, compared to the 45.6% (N = 1,017) covered in CrossRef. While making up only 17.% of all the African journals, South African journals had the best coverage in the two most authoritative databases, accounting for 73.5% and 62.1% of all the African journals in Web of Science and Scopus, respectively. In contrast, Nigeria published 44.5% of all the African journals. The distribution of the African journals is biased in favor of Medical, Life and Health Sciences and Humanities and the Arts in the three databases. The low representation of African journals in CrossRef, a free indexing infrastructure that could be harnessed for building an African-centric research indexing database, is concerning.
    Date
    22. 6.2023 14:09:06
    Object
    Web of Science
  4. Crespo, J.A.; Herranz, N.; Li, Y.; Ruiz-Castillo, J.: ¬The effect on citation inequality of differences in citation practices at the web of science subject category level (2014) 0.01
    0.0064596576 = product of:
      0.029068459 = sum of:
        0.014982964 = product of:
          0.029965928 = sum of:
            0.029965928 = weight(_text_:web in 1291) [ClassicSimilarity], result of:
              0.029965928 = score(doc=1291,freq=6.0), product of:
                0.09596372 = queryWeight, product of:
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.02940506 = queryNorm
                0.3122631 = fieldWeight in 1291, product of:
                  2.4494898 = tf(freq=6.0), with freq of:
                    6.0 = termFreq=6.0
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=1291)
          0.5 = coord(1/2)
        0.014085495 = product of:
          0.02817099 = sum of:
            0.02817099 = weight(_text_:22 in 1291) [ClassicSimilarity], result of:
              0.02817099 = score(doc=1291,freq=4.0), product of:
                0.10297151 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.02940506 = queryNorm
                0.27358043 = fieldWeight in 1291, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=1291)
          0.5 = coord(1/2)
      0.22222222 = coord(2/9)
    
    Abstract
    This article studies the impact of differences in citation practices at the subfield, or Web of Science subject category level, using the model introduced in Crespo, Li, and Ruiz-Castillo (2013a), according to which the number of citations received by an article depends on its underlying scientific influence and the field to which it belongs. We use the same Thomson Reuters data set of about 4.4 million articles used in Crespo et al. (2013a) to analyze 22 broad fields. The main results are the following: First, when the classification system goes from 22 fields to 219 subfields the effect on citation inequality of differences in citation practices increases from ?14% at the field level to 18% at the subfield level. Second, we estimate a set of exchange rates (ERs) over a wide [660, 978] citation quantile interval to express the citation counts of articles into the equivalent counts in the all-sciences case. In the fractional case, for example, we find that in 187 of 219 subfields the ERs are reliable in the sense that the coefficient of variation is smaller than or equal to 0.10. Third, in the fractional case the normalization of the raw data using the ERs (or subfield mean citations) as normalization factors reduces the importance of the differences in citation practices from 18% to 3.8% (3.4%) of overall citation inequality. Fourth, the results in the fractional case are essentially replicated when we adopt a multiplicative approach.
    Object
    Web of Science
  5. Zhu, Q.; Kong, X.; Hong, S.; Li, J.; He, Z.: Global ontology research progress : a bibliometric analysis (2015) 0.01
    0.0064596576 = product of:
      0.029068459 = sum of:
        0.014982964 = product of:
          0.029965928 = sum of:
            0.029965928 = weight(_text_:web in 2590) [ClassicSimilarity], result of:
              0.029965928 = score(doc=2590,freq=6.0), product of:
                0.09596372 = queryWeight, product of:
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.02940506 = queryNorm
                0.3122631 = fieldWeight in 2590, product of:
                  2.4494898 = tf(freq=6.0), with freq of:
                    6.0 = termFreq=6.0
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=2590)
          0.5 = coord(1/2)
        0.014085495 = product of:
          0.02817099 = sum of:
            0.02817099 = weight(_text_:22 in 2590) [ClassicSimilarity], result of:
              0.02817099 = score(doc=2590,freq=4.0), product of:
                0.10297151 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.02940506 = queryNorm
                0.27358043 = fieldWeight in 2590, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=2590)
          0.5 = coord(1/2)
      0.22222222 = coord(2/9)
    
    Abstract
    Purpose - The purpose of this paper is to analyse the global scientific outputs of ontology research, an important emerging discipline that has huge potential to improve information understanding, organization, and management. Design/methodology/approach - This study collected literature published during 1900-2012 from the Web of Science database. The bibliometric analysis was performed from authorial, institutional, national, spatiotemporal, and topical aspects. Basic statistical analysis, visualization of geographic distribution, co-word analysis, and a new index were applied to the selected data. Findings - Characteristics of publication outputs suggested that ontology research has entered into the soaring stage, along with increased participation and collaboration. The authors identified the leading authors, institutions, nations, and articles in ontology research. Authors were more from North America, Europe, and East Asia. The USA took the lead, while China grew fastest. Four major categories of frequently used keywords were identified: applications in Semantic Web, applications in bioinformatics, philosophy theories, and common supporting technology. Semantic Web research played a core role, and gene ontology study was well-developed. The study focus of ontology has shifted from philosophy to information science. Originality/value - This is the first study to quantify global research patterns and trends in ontology, which might provide a potential guide for the future research. The new index provides an alternative way to evaluate the multidisciplinary influence of researchers.
    Date
    20. 1.2015 18:30:22
    17. 9.2018 18:22:23
  6. Larivière, V.; Gingras, Y.; Archambault, E.: ¬The decline in the concentration of citations, 1900-2007 (2009) 0.01
    0.0060629104 = product of:
      0.027283097 = sum of:
        0.010380501 = product of:
          0.020761002 = sum of:
            0.020761002 = weight(_text_:web in 2763) [ClassicSimilarity], result of:
              0.020761002 = score(doc=2763,freq=2.0), product of:
                0.09596372 = queryWeight, product of:
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.02940506 = queryNorm
                0.21634221 = fieldWeight in 2763, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.046875 = fieldNorm(doc=2763)
          0.5 = coord(1/2)
        0.016902596 = product of:
          0.03380519 = sum of:
            0.03380519 = weight(_text_:22 in 2763) [ClassicSimilarity], result of:
              0.03380519 = score(doc=2763,freq=4.0), product of:
                0.10297151 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.02940506 = queryNorm
                0.32829654 = fieldWeight in 2763, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.046875 = fieldNorm(doc=2763)
          0.5 = coord(1/2)
      0.22222222 = coord(2/9)
    
    Abstract
    This article challenges recent research (Evans, 2008) reporting that the concentration of cited scientific literature increases with the online availability of articles and journals. Using Thomson Reuters' Web of Science, the present article analyses changes in the concentration of citations received (2- and 5-year citation windows) by papers published between 1900 and 2005. Three measures of concentration are used: the percentage of papers that received at least one citation (cited papers); the percentage of papers needed to account for 20%, 50%, and 80% of the citations; and the Herfindahl-Hirschman index (HHI). These measures are used for four broad disciplines: natural sciences and engineering, medical fields, social sciences, and the humanities. All these measures converge and show that, contrary to what was reported by Evans, the dispersion of citations is actually increasing.
    Date
    22. 3.2009 19:22:35
  7. Zhang, Y.; Jansen, B.J.; Spink, A.: Identification of factors predicting clickthrough in Web searching using neural network analysis (2009) 0.01
    0.005918263 = product of:
      0.026632184 = sum of:
        0.014680246 = product of:
          0.029360492 = sum of:
            0.029360492 = weight(_text_:web in 2742) [ClassicSimilarity], result of:
              0.029360492 = score(doc=2742,freq=4.0), product of:
                0.09596372 = queryWeight, product of:
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.02940506 = queryNorm
                0.3059541 = fieldWeight in 2742, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.046875 = fieldNorm(doc=2742)
          0.5 = coord(1/2)
        0.011951938 = product of:
          0.023903877 = sum of:
            0.023903877 = weight(_text_:22 in 2742) [ClassicSimilarity], result of:
              0.023903877 = score(doc=2742,freq=2.0), product of:
                0.10297151 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.02940506 = queryNorm
                0.23214069 = fieldWeight in 2742, 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=2742)
          0.5 = coord(1/2)
      0.22222222 = coord(2/9)
    
    Abstract
    In this research, we aim to identify factors that significantly affect the clickthrough of Web searchers. Our underlying goal is determine more efficient methods to optimize the clickthrough rate. We devise a clickthrough metric for measuring customer satisfaction of search engine results using the number of links visited, number of queries a user submits, and rank of clicked links. We use a neural network to detect the significant influence of searching characteristics on future user clickthrough. Our results show that high occurrences of query reformulation, lengthy searching duration, longer query length, and the higher ranking of prior clicked links correlate positively with future clickthrough. We provide recommendations for leveraging these findings for improving the performance of search engine retrieval and result ranking, along with implications for search engine marketing.
    Date
    22. 3.2009 17:49:11
  8. Neth, M.: Citation analysis and the Web (1998) 0.01
    0.005789892 = product of:
      0.026054513 = sum of:
        0.012110585 = product of:
          0.02422117 = sum of:
            0.02422117 = weight(_text_:web in 108) [ClassicSimilarity], result of:
              0.02422117 = score(doc=108,freq=2.0), product of:
                0.09596372 = queryWeight, product of:
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.02940506 = queryNorm
                0.25239927 = fieldWeight in 108, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.0546875 = fieldNorm(doc=108)
          0.5 = coord(1/2)
        0.013943928 = product of:
          0.027887857 = sum of:
            0.027887857 = weight(_text_:22 in 108) [ClassicSimilarity], result of:
              0.027887857 = score(doc=108,freq=2.0), product of:
                0.10297151 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.02940506 = queryNorm
                0.2708308 = fieldWeight in 108, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.0546875 = fieldNorm(doc=108)
          0.5 = coord(1/2)
      0.22222222 = coord(2/9)
    
    Date
    10. 1.1999 16:22:37
  9. Ding, Y.: Applying weighted PageRank to author citation networks (2011) 0.01
    0.005789892 = product of:
      0.026054513 = sum of:
        0.012110585 = product of:
          0.02422117 = sum of:
            0.02422117 = weight(_text_:web in 4188) [ClassicSimilarity], result of:
              0.02422117 = score(doc=4188,freq=2.0), product of:
                0.09596372 = queryWeight, product of:
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.02940506 = queryNorm
                0.25239927 = fieldWeight in 4188, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.0546875 = fieldNorm(doc=4188)
          0.5 = coord(1/2)
        0.013943928 = product of:
          0.027887857 = sum of:
            0.027887857 = weight(_text_:22 in 4188) [ClassicSimilarity], result of:
              0.027887857 = score(doc=4188,freq=2.0), product of:
                0.10297151 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.02940506 = queryNorm
                0.2708308 = fieldWeight in 4188, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.0546875 = fieldNorm(doc=4188)
          0.5 = coord(1/2)
      0.22222222 = coord(2/9)
    
    Abstract
    This article aims to identify whether different weighted PageRank algorithms can be applied to author citation networks to measure the popularity and prestige of a scholar from a citation perspective. Information retrieval (IR) was selected as a test field and data from 1956-2008 were collected from Web of Science. Weighted PageRank with citation and publication as weighted vectors were calculated on author citation networks. The results indicate that both popularity rank and prestige rank were highly correlated with the weighted PageRank. Principal component analysis was conducted to detect relationships among these different measures. For capturing prize winners within the IR field, prestige rank outperformed all the other measures
    Date
    22. 1.2011 13:02:21
  10. Levitt, J.M.; Thelwall, M.: Citation levels and collaboration within library and information science (2009) 0.01
    0.005052425 = product of:
      0.022735912 = sum of:
        0.008650418 = product of:
          0.017300837 = sum of:
            0.017300837 = weight(_text_:web in 2734) [ClassicSimilarity], result of:
              0.017300837 = score(doc=2734,freq=2.0), product of:
                0.09596372 = queryWeight, product of:
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.02940506 = queryNorm
                0.18028519 = fieldWeight in 2734, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=2734)
          0.5 = coord(1/2)
        0.014085495 = product of:
          0.02817099 = sum of:
            0.02817099 = weight(_text_:22 in 2734) [ClassicSimilarity], result of:
              0.02817099 = score(doc=2734,freq=4.0), product of:
                0.10297151 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.02940506 = queryNorm
                0.27358043 = fieldWeight in 2734, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=2734)
          0.5 = coord(1/2)
      0.22222222 = coord(2/9)
    
    Abstract
    Collaboration is a major research policy objective, but does it deliver higher quality research? This study uses citation analysis to examine the Web of Science (WoS) Information Science & Library Science subject category (IS&LS) to ascertain whether, in general, more highly cited articles are more highly collaborative than other articles. It consists of two investigations. The first investigation is a longitudinal comparison of the degree and proportion of collaboration in five strata of citation; it found that collaboration in the highest four citation strata (all in the most highly cited 22%) increased in unison over time, whereas collaboration in the lowest citation strata (un-cited articles) remained low and stable. Given that over 40% of the articles were un-cited, it seems important to take into account the differences found between un-cited articles and relatively highly cited articles when investigating collaboration in IS&LS. The second investigation compares collaboration for 35 influential information scientists; it found that their more highly cited articles on average were not more highly collaborative than their less highly cited articles. In summary, although collaborative research is conducive to high citation in general, collaboration has apparently not tended to be essential to the success of current and former elite information scientists.
    Date
    22. 3.2009 12:43:51
  11. He, Z.-L.: International collaboration does not have greater epistemic authority (2009) 0.00
    0.004962764 = product of:
      0.02233244 = sum of:
        0.010380501 = product of:
          0.020761002 = sum of:
            0.020761002 = weight(_text_:web in 3122) [ClassicSimilarity], result of:
              0.020761002 = score(doc=3122,freq=2.0), product of:
                0.09596372 = queryWeight, product of:
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.02940506 = queryNorm
                0.21634221 = fieldWeight in 3122, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.046875 = fieldNorm(doc=3122)
          0.5 = coord(1/2)
        0.011951938 = product of:
          0.023903877 = sum of:
            0.023903877 = weight(_text_:22 in 3122) [ClassicSimilarity], result of:
              0.023903877 = score(doc=3122,freq=2.0), product of:
                0.10297151 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.02940506 = queryNorm
                0.23214069 = fieldWeight in 3122, 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=3122)
          0.5 = coord(1/2)
      0.22222222 = coord(2/9)
    
    Abstract
    The consistent finding that internationally coauthored papers are more heavily cited has led to a tacit agreement among politicians and scientists that international collaboration in scientific research should be particularly promoted. However, existing studies of research collaboration suffer from a major weakness in that the Thomson Reuters Web of Science until recently did not link author names with affiliation addresses. The general approach has been to hierarchically code papers into international paper, national paper, or local paper based on the address information. This hierarchical coding scheme severely understates the level and contribution of local or national collaboration on an internationally coauthored paper. In this research, I code collaboration variables by hand checking each paper in the sample, use two measures of a paper's impact, and try several regression models. I find that both international collaboration and local collaboration are positively and significantly associated with a paper's impact, but international collaboration does not have more epistemic authority than local collaboration. This result suggests that previous findings based on hierarchical coding might be misleading.
    Date
    26. 9.2009 11:22:05
  12. Li, J.; Shi, D.: Sleeping beauties in genius work : when were they awakened? (2016) 0.00
    0.004962764 = product of:
      0.02233244 = sum of:
        0.010380501 = product of:
          0.020761002 = sum of:
            0.020761002 = weight(_text_:web in 2647) [ClassicSimilarity], result of:
              0.020761002 = score(doc=2647,freq=2.0), product of:
                0.09596372 = queryWeight, product of:
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.02940506 = queryNorm
                0.21634221 = fieldWeight in 2647, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.046875 = fieldNorm(doc=2647)
          0.5 = coord(1/2)
        0.011951938 = product of:
          0.023903877 = sum of:
            0.023903877 = weight(_text_:22 in 2647) [ClassicSimilarity], result of:
              0.023903877 = score(doc=2647,freq=2.0), product of:
                0.10297151 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.02940506 = queryNorm
                0.23214069 = fieldWeight in 2647, 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=2647)
          0.5 = coord(1/2)
      0.22222222 = coord(2/9)
    
    Abstract
    "Genius work," proposed by Avramescu, refers to scientific articles whose citations grow exponentially in an extended period, for example, over 50 years. Such articles were defined as "sleeping beauties" by van Raan, who quantitatively studied the phenomenon of delayed recognition. However, the criteria adopted by van Raan at times are not applicable and may confer recognition prematurely. To revise such deficiencies, this paper proposes two new criteria, which are applicable (but not limited) to exponential citation curves. We searched for genius work among articles of Nobel Prize laureates during the period of 1901-2012 on the Web of Science, finding 25 articles of genius work out of 21,438 papers including 10 (by van Raan's criteria) sleeping beauties and 15 nonsleeping-beauties. By our new criteria, two findings were obtained through empirical analysis: (a) the awakening periods for genius work depend on the increase rate b in the exponential function, and (b) lower b leads to a longer sleeping period.
    Date
    22. 1.2016 14:13:32
  13. Ridenour, L.: Boundary objects : measuring gaps and overlap between research areas (2016) 0.00
    0.004962764 = product of:
      0.02233244 = sum of:
        0.010380501 = product of:
          0.020761002 = sum of:
            0.020761002 = weight(_text_:web in 2835) [ClassicSimilarity], result of:
              0.020761002 = score(doc=2835,freq=2.0), product of:
                0.09596372 = queryWeight, product of:
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.02940506 = queryNorm
                0.21634221 = fieldWeight in 2835, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.046875 = fieldNorm(doc=2835)
          0.5 = coord(1/2)
        0.011951938 = product of:
          0.023903877 = sum of:
            0.023903877 = weight(_text_:22 in 2835) [ClassicSimilarity], result of:
              0.023903877 = score(doc=2835,freq=2.0), product of:
                0.10297151 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.02940506 = queryNorm
                0.23214069 = fieldWeight in 2835, 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=2835)
          0.5 = coord(1/2)
      0.22222222 = coord(2/9)
    
    Abstract
    The aim of this paper is to develop methodology to determine conceptual overlap between research areas. It investigates patterns of terminology usage in scientific abstracts as boundary objects between research specialties. Research specialties were determined by high-level classifications assigned by Thomson Reuters in their Essential Science Indicators file, which provided a strictly hierarchical classification of journals into 22 categories. Results from the query "network theory" were downloaded from the Web of Science. From this file, two top-level groups, economics and social sciences, were selected and topically analyzed to provide a baseline of similarity on which to run an informetric analysis. The Places & Spaces Map of Science (Klavans and Boyack 2007) was used to determine the proximity of disciplines to one another in order to select the two disciplines use in the analysis. Groups analyzed share common theories and goals; however, groups used different language to describe their research. It was found that 61% of term words were shared between the two groups.
  14. Leydesdorff, L.; Bornmann, L.; Wagner, C.S.: ¬The relative influences of government funding and international collaboration on citation impact (2019) 0.00
    0.004962764 = product of:
      0.02233244 = sum of:
        0.010380501 = product of:
          0.020761002 = sum of:
            0.020761002 = weight(_text_:web in 4681) [ClassicSimilarity], result of:
              0.020761002 = score(doc=4681,freq=2.0), product of:
                0.09596372 = queryWeight, product of:
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.02940506 = queryNorm
                0.21634221 = fieldWeight in 4681, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.046875 = fieldNorm(doc=4681)
          0.5 = coord(1/2)
        0.011951938 = product of:
          0.023903877 = sum of:
            0.023903877 = weight(_text_:22 in 4681) [ClassicSimilarity], result of:
              0.023903877 = score(doc=4681,freq=2.0), product of:
                0.10297151 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.02940506 = queryNorm
                0.23214069 = fieldWeight in 4681, 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=4681)
          0.5 = coord(1/2)
      0.22222222 = coord(2/9)
    
    Abstract
    A recent publication in Nature reports that public R&D funding is only weakly correlated with the citation impact of a nation's articles as measured by the field-weighted citation index (FWCI; defined by Scopus). On the basis of the supplementary data, we up-scaled the design using Web of Science data for the decade 2003-2013 and OECD funding data for the corresponding decade assuming a 2-year delay (2001-2011). Using negative binomial regression analysis, we found very small coefficients, but the effects of international collaboration are positive and statistically significant, whereas the effects of government funding are negative, an order of magnitude smaller, and statistically nonsignificant (in two of three analyses). In other words, international collaboration improves the impact of research articles, whereas more government funding tends to have a small adverse effect when comparing OECD countries.
    Date
    8. 1.2019 18:22:45
  15. Stuart, D.: Web metrics for library and information professionals (2014) 0.00
    0.004308088 = product of:
      0.038772795 = sum of:
        0.038772795 = product of:
          0.07754559 = sum of:
            0.07754559 = weight(_text_:web in 2274) [ClassicSimilarity], result of:
              0.07754559 = score(doc=2274,freq=82.0), product of:
                0.09596372 = queryWeight, product of:
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.02940506 = queryNorm
                0.808072 = fieldWeight in 2274, product of:
                  9.055386 = tf(freq=82.0), with freq of:
                    82.0 = termFreq=82.0
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.02734375 = fieldNorm(doc=2274)
          0.5 = coord(1/2)
      0.11111111 = coord(1/9)
    
    Abstract
    This is a practical guide to using web metrics to measure impact and demonstrate value. The web provides an opportunity to collect a host of different metrics, from those associated with social media accounts and websites to more traditional research outputs. This book is a clear guide for library and information professionals as to what web metrics are available and how to assess and use them to make informed decisions and demonstrate value. As individuals and organizations increasingly use the web in addition to traditional publishing avenues and formats, this book provides the tools to unlock web metrics and evaluate the impact of this content. The key topics covered include: bibliometrics, webometrics and web metrics; data collection tools; evaluating impact on the web; evaluating social media impact; investigating relationships between actors; exploring traditional publications in a new environment; web metrics and the web of data; the future of web metrics and the library and information professional. The book will provide a practical introduction to web metrics for a wide range of library and information professionals, from the bibliometrician wanting to demonstrate the wider impact of a researcher's work than can be demonstrated through traditional citations databases, to the reference librarian wanting to measure how successfully they are engaging with their users on Twitter. It will be a valuable tool for anyone who wants to not only understand the impact of content, but demonstrate this impact to others within the organization and beyond.
    Content
    1. Introduction. MetricsIndicators -- Web metrics and Ranganathan's laws of library science -- Web metrics for the library and information professional -- The aim of this book -- The structure of the rest of this book -- 2. Bibliometrics, webometrics and web metrics. Web metrics -- Information science metrics -- Web analytics -- Relational and evaluative metrics -- Evaluative web metrics -- Relational web metrics -- Validating the results -- 3. Data collection tools. The anatomy of a URL, web links and the structure of the web -- Search engines 1.0 -- Web crawlers -- Search engines 2.0 -- Post search engine 2.0: fragmentation -- 4. Evaluating impact on the web. Websites -- Blogs -- Wikis -- Internal metrics -- External metrics -- A systematic approach to content analysis -- 5. Evaluating social media impact. Aspects of social network sites -- Typology of social network sites -- Research and tools for specific sites and services -- Other social network sites -- URL shorteners: web analytic links on any site -- General social media impact -- Sentiment analysis -- 6. Investigating relationships between actors. Social network analysis methods -- Sources for relational network analysis -- 7. Exploring traditional publications in a new environment. More bibliographic items -- Full text analysis -- Greater context -- 8. Web metrics and the web of data. The web of data -- Building the semantic web -- Implications of the web of data for web metrics -- Investigating the web of data today -- SPARQL -- Sindice -- LDSpider: an RDF web crawler -- 9. The future of web metrics and the library and information professional. How far we have come -- The future of web metrics -- The future of the library and information professional and web metrics.
    RSWK
    Bibliothek / World Wide Web / World Wide Web 2.0 / Analyse / Statistik
    Bibliometrie / Semantic Web / Soziale Software
    Subject
    Bibliothek / World Wide Web / World Wide Web 2.0 / Analyse / Statistik
    Bibliometrie / Semantic Web / Soziale Software
  16. Mukherjee, B.: Do open-access journals in library and information science have any scholarly impact? : a bibliometric study of selected open-access journals using Google Scholar (2009) 0.00
    0.004135637 = product of:
      0.018610368 = sum of:
        0.008650418 = product of:
          0.017300837 = sum of:
            0.017300837 = weight(_text_:web in 2745) [ClassicSimilarity], result of:
              0.017300837 = score(doc=2745,freq=2.0), product of:
                0.09596372 = queryWeight, product of:
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.02940506 = queryNorm
                0.18028519 = fieldWeight in 2745, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=2745)
          0.5 = coord(1/2)
        0.009959949 = product of:
          0.019919898 = sum of:
            0.019919898 = weight(_text_:22 in 2745) [ClassicSimilarity], result of:
              0.019919898 = score(doc=2745,freq=2.0), product of:
                0.10297151 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.02940506 = queryNorm
                0.19345059 = fieldWeight in 2745, 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=2745)
          0.5 = coord(1/2)
      0.22222222 = coord(2/9)
    
    Abstract
    Using 17 fully open-access journals published uninterruptedly during 2000 to 2004 in the field of library and information science, the present study investigates the impact of these open-access journals in terms of quantity of articles published, subject distribution of the articles, synchronous and diachronous impact factor, immediacy index, and journals' and authors' self-citation. The results indicate that during this 5-year publication period, there are as many as 1,636 articles published by these journals. At the same time, the articles have received a total of 8,591 Web citations during a 7-year citation period. Eight of 17 journals have received more than 100 citations. First Monday received the highest number of citations; however, the average number of citations per article was the highest in D-Lib Magazine. The value of the synchronous impact factor varies from 0.6989 to 1.0014 during 2002 to 2005, and the diachronous impact factor varies from 1.472 to 2.487 during 2000 to 2004. The range of the immediacy index varies between 0.0714 and 1.395. D-Lib Magazine has an immediacy index value above 0.5 in all the years whereas the immediacy index value varies from year to year for the other journals. When the citations of sample articles were analyzed according to source, it was found that 40.32% of the citations came from full-text articles, followed by 33.35% from journal articles. The percentage of journals' self-citation was only 6.04%.
    Date
    22. 3.2009 17:54:59
  17. Heneberg, P.: Supposedly uncited articles of Nobel laureates and Fields medalists can be prevalently attributed to the errors of omission and commission (2013) 0.00
    0.004135637 = product of:
      0.018610368 = sum of:
        0.008650418 = product of:
          0.017300837 = sum of:
            0.017300837 = weight(_text_:web in 660) [ClassicSimilarity], result of:
              0.017300837 = score(doc=660,freq=2.0), product of:
                0.09596372 = queryWeight, product of:
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.02940506 = queryNorm
                0.18028519 = fieldWeight in 660, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=660)
          0.5 = coord(1/2)
        0.009959949 = product of:
          0.019919898 = sum of:
            0.019919898 = weight(_text_:22 in 660) [ClassicSimilarity], result of:
              0.019919898 = score(doc=660,freq=2.0), product of:
                0.10297151 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.02940506 = queryNorm
                0.19345059 = fieldWeight in 660, 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=660)
          0.5 = coord(1/2)
      0.22222222 = coord(2/9)
    
    Abstract
    Several independent authors reported a high share of uncited publications, which include those produced by top scientists. This share was repeatedly reported to exceed 10% of the total papers produced, without any explanation of this phenomenon and the lack of difference in uncitedness between average and successful researchers. In this report, we analyze the uncitedness among two independent groups of highly visible scientists (mathematicians represented by Fields medalists, and researchers in physiology or medicine represented by Nobel Prize laureates in the respective field). Analysis of both groups led to the identical conclusion: over 90% of the uncited database records of highly visible scientists can be explained by the inclusion of editorial materials progress reports presented at international meetings (meeting abstracts), discussion items (letters to the editor, discussion), personalia (biographic items), and by errors of omission and commission of the Web of Science (WoS) database and of the citing documents. Only a marginal amount of original articles and reviews were found to be uncited (0.9 and 0.3%, respectively), which is in strong contrast with the previously reported data, which never addressed the document types among the uncited records.
    Date
    22. 3.2013 19:21:46
  18. Lercher, A.: Correlation over time for citations to mathematics articles (2013) 0.00
    0.004135637 = product of:
      0.018610368 = sum of:
        0.008650418 = product of:
          0.017300837 = sum of:
            0.017300837 = weight(_text_:web in 661) [ClassicSimilarity], result of:
              0.017300837 = score(doc=661,freq=2.0), product of:
                0.09596372 = queryWeight, product of:
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.02940506 = queryNorm
                0.18028519 = fieldWeight in 661, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=661)
          0.5 = coord(1/2)
        0.009959949 = product of:
          0.019919898 = sum of:
            0.019919898 = weight(_text_:22 in 661) [ClassicSimilarity], result of:
              0.019919898 = score(doc=661,freq=2.0), product of:
                0.10297151 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.02940506 = queryNorm
                0.19345059 = fieldWeight in 661, 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=661)
          0.5 = coord(1/2)
      0.22222222 = coord(2/9)
    
    Abstract
    Explicit definition of the limits of citation analysis demands additional tests for the validity of citation analysis. The stability of citation rankings over time can be regarded as confirming the validity of evaluative citation analysis. This stability over time was investigated for two sets of citation records from the Web of Science (Thomson Reuters, Philadelphia, PA) for articles published in journals classified in Journal Citation Reports as Mathematics. These sets are of all such articles for the 1960s and for the 1970s. This study employs only descriptive statistics and draws no inferences to any larger population. The study found a high correlation from one decade to the next of rankings among sets of most highly cited articles. However, the study found a low correlation for rankings among articles whose ranks were the 500 directly below those of the 500 most cited. This perhaps expected result is discussed in terms of the Glänzel-Schubert-Schoepflin stochastic model for citation processes and also in connection with an account of the purposes of evaluative citation analysis. This interpretative context suggests why the limitations of citation analysis may be inherent to citation analysis even when it is done well.
    Date
    22. 3.2013 19:23:35
  19. Costas, R.; Zahedi, Z.; Wouters, P.: ¬The thematic orientation of publications mentioned on social media : large-scale disciplinary comparison of social media metrics with citations (2015) 0.00
    0.004135637 = product of:
      0.018610368 = sum of:
        0.008650418 = product of:
          0.017300837 = sum of:
            0.017300837 = weight(_text_:web in 2598) [ClassicSimilarity], result of:
              0.017300837 = score(doc=2598,freq=2.0), product of:
                0.09596372 = queryWeight, product of:
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.02940506 = queryNorm
                0.18028519 = fieldWeight in 2598, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=2598)
          0.5 = coord(1/2)
        0.009959949 = product of:
          0.019919898 = sum of:
            0.019919898 = weight(_text_:22 in 2598) [ClassicSimilarity], result of:
              0.019919898 = score(doc=2598,freq=2.0), product of:
                0.10297151 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.02940506 = queryNorm
                0.19345059 = fieldWeight in 2598, 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=2598)
          0.5 = coord(1/2)
      0.22222222 = coord(2/9)
    
    Abstract
    Purpose - The purpose of this paper is to analyze the disciplinary orientation of scientific publications that were mentioned on different social media platforms, focussing on their differences and similarities with citation counts. Design/methodology/approach - Social media metrics and readership counts, associated with 500,216 publications and their citation data from the Web of Science database, were collected from Altmetric.com and Mendeley. Results are presented through descriptive statistical analyses together with science maps generated with VOSviewer. Findings - The results confirm Mendeley as the most prevalent social media source with similar characteristics to citations in their distribution across fields and their density in average values per publication. The humanities, natural sciences, and engineering disciplines have a much lower presence of social media metrics. Twitter has a stronger focus on general medicine and social sciences. Other sources (blog, Facebook, Google+, and news media mentions) are more prominent in regards to multidisciplinary journals. Originality/value - This paper reinforces the relevance of Mendeley as a social media source for analytical purposes from a disciplinary perspective, being particularly relevant for the social sciences (together with Twitter). Key implications for the use of social media metrics on the evaluation of research performance (e.g. the concentration of some social media metrics, such as blogs, news items, etc., around multidisciplinary journals) are identified.
    Date
    20. 1.2015 18:30:22
  20. Thelwall, M.; Thelwall, S.: ¬A thematic analysis of highly retweeted early COVID-19 tweets : consensus, information, dissent and lockdown life (2020) 0.00
    0.004135637 = product of:
      0.018610368 = sum of:
        0.008650418 = product of:
          0.017300837 = sum of:
            0.017300837 = weight(_text_:web in 178) [ClassicSimilarity], result of:
              0.017300837 = score(doc=178,freq=2.0), product of:
                0.09596372 = queryWeight, product of:
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.02940506 = queryNorm
                0.18028519 = fieldWeight in 178, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.2635105 = idf(docFreq=4597, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=178)
          0.5 = coord(1/2)
        0.009959949 = product of:
          0.019919898 = sum of:
            0.019919898 = weight(_text_:22 in 178) [ClassicSimilarity], result of:
              0.019919898 = score(doc=178,freq=2.0), product of:
                0.10297151 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.02940506 = queryNorm
                0.19345059 = fieldWeight in 178, 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=178)
          0.5 = coord(1/2)
      0.22222222 = coord(2/9)
    
    Abstract
    Purpose Public attitudes towards COVID-19 and social distancing are critical in reducing its spread. It is therefore important to understand public reactions and information dissemination in all major forms, including on social media. This article investigates important issues reflected on Twitter in the early stages of the public reaction to COVID-19. Design/methodology/approach A thematic analysis of the most retweeted English-language tweets mentioning COVID-19 during March 10-29, 2020. Findings The main themes identified for the 87 qualifying tweets accounting for 14 million retweets were: lockdown life; attitude towards social restrictions; politics; safety messages; people with COVID-19; support for key workers; work; and COVID-19 facts/news. Research limitations/implications Twitter played many positive roles, mainly through unofficial tweets. Users shared social distancing information, helped build support for social distancing, criticised government responses, expressed support for key workers and helped each other cope with social isolation. A few popular tweets not supporting social distancing show that government messages sometimes failed. Practical implications Public health campaigns in future may consider encouraging grass roots social web activity to support campaign goals. At a methodological level, analysing retweet counts emphasised politics and ignored practical implementation issues. Originality/value This is the first qualitative analysis of general COVID-19-related retweeting.
    Date
    20. 1.2015 18:30:22

Years

Types

  • a 316
  • el 7
  • m 5
  • s 2
  • x 1
  • More… Less…