Search (15 results, page 1 of 1)

0.023835853 = product of:
  0.047671705 = sum of:
    0.047671705 = product of:
      0.09534341 = sum of:
        0.09534341 = weight(_text_:e.g in 382) [ClassicSimilarity], result of:
          0.09534341 = score(doc=382,freq=4.0), product of:
            0.23393378 = queryWeight, product of:
              5.2168427 = idf(docFreq=651, maxDocs=44218)
              0.044842023 = queryNorm
            0.40756583 = fieldWeight in 382, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              5.2168427 = idf(docFreq=651, maxDocs=44218)
              0.0390625 = fieldNorm(doc=382)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Although there is some evidence that online videos are increasingly used by academics for informal scholarly communication and teaching, the extent to which they are used in published academic research is unknown. This article explores the extent to which YouTube videos are cited in academic publications and whether there are significant broad disciplinary differences in this practice. To investigate, we extracted the URL citations to YouTube videos from academic publications indexed by Scopus. A total of 1,808 Scopus publications cited at least one YouTube video, and there was a steady upward growth in citing online videos within scholarly publications from 2006 to 2011, with YouTube citations being most common within arts and humanities (0.3%) and the social sciences (0.2%). A content analysis of 551 YouTube videos cited by research articles indicated that in science (78%) and in medicine and health sciences (77%), over three fourths of the cited videos had either direct scientific (e.g., laboratory experiments) or scientific-related contents (e.g., academic lectures or education) whereas in the arts and humanities, about 80% of the YouTube videos had art, culture, or history themes, and in the social sciences, about 63% of the videos were related to news, politics, advertisements, and documentaries. This shows both the disciplinary differences and the wide variety of innovative research communication uses found for videos within the different subject areas.

0.020225393 = product of:
  0.040450785 = sum of:
    0.040450785 = product of:
      0.08090157 = sum of:
        0.08090157 = weight(_text_:e.g in 414) [ClassicSimilarity], result of:
          0.08090157 = score(doc=414,freq=2.0), product of:
            0.23393378 = queryWeight, product of:
              5.2168427 = idf(docFreq=651, maxDocs=44218)
              0.044842023 = queryNorm
            0.34583107 = fieldWeight in 414, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              5.2168427 = idf(docFreq=651, maxDocs=44218)
              0.046875 = fieldNorm(doc=414)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

As one of the world's most visited websites, YouTube is potentially influential for learning gendered attitudes. Nevertheless, despite evidence of gender influences within the site for some topics, the extent to which YouTube reflects or promotes male/female or other gender divides is unknown. This article analyses 10,211 YouTube videos published in 12 months from 2014 to 2015 using commenter-portrayed genders (inferred from usernames) and view counts from the end of 2019. Nonbinary genders are omitted for methodological reasons. Although there were highly male and female topics or themes (e.g., vehicles or beauty) and male or female gendering is the norm, videos with topics attracting both males and females tended to have more viewers (after approximately 5 years) than videos in male or female gendered topics. Similarly, within each topic, videos with gender balanced sets of commenters tend to attract more viewers. Thus, YouTube does not seem to be driving male-female gender differences.

0.016854495 = product of:
  0.03370899 = sum of:
    0.03370899 = product of:
      0.06741798 = sum of:
        0.06741798 = weight(_text_:e.g in 4279) [ClassicSimilarity], result of:
          0.06741798 = score(doc=4279,freq=2.0), product of:
            0.23393378 = queryWeight, product of:
              5.2168427 = idf(docFreq=651, maxDocs=44218)
              0.044842023 = queryNorm
            0.28819257 = fieldWeight in 4279, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              5.2168427 = idf(docFreq=651, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4279)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Webometrics, the quantitative study of Web-related phenomena, emerged from the realization that methods originally designed for bibliometric analysis of scientific journal article citation patterns could be applied to the Web, with commercial search engines providing the raw data. Almind and Ingwersen (1997) defined the field and gave it its name. Other pioneers included Rodriguez Gairin (1997) and Aguillo (1998). Larson (1996) undertook exploratory link structure analysis, as did Rousseau (1997). Webometrics encompasses research from fields beyond information science such as communication studies, statistical physics, and computer science. In this review we concentrate on link analysis, but also cover other aspects of webometrics, including Web log fle analysis. One theme that runs through this chapter is the messiness of Web data and the need for data cleansing heuristics. The uncontrolled Web creates numerous problems in the interpretation of results, for instance, from the automatic creation or replication of links. The loose connection between top-level domain specifications (e.g., com, edu, and org) and their actual content is also a frustrating problem. For example, many .com sites contain noncommercial content, although com is ostensibly the main commercial top-level domain. Indeed, a skeptical researcher could claim that obstacles of this kind are so great that all Web analyses lack value. As will be seen, one response to this view, a view shared by critics of evaluative bibliometrics, is to demonstrate that Web data correlate significantly with some non-Web data in order to prove that the Web data are not wholly random. A practical response has been to develop increasingly sophisticated data cleansing techniques and multiple data analysis methods.

0.016854495 = product of:
  0.03370899 = sum of:
    0.03370899 = product of:
      0.06741798 = sum of:
        0.06741798 = weight(_text_:e.g in 157) [ClassicSimilarity], result of:
          0.06741798 = score(doc=157,freq=2.0), product of:
            0.23393378 = queryWeight, product of:
              5.2168427 = idf(docFreq=651, maxDocs=44218)
              0.044842023 = queryNorm
            0.28819257 = fieldWeight in 157, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              5.2168427 = idf(docFreq=651, maxDocs=44218)
              0.0390625 = fieldNorm(doc=157)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Finding new ways to help researchers and administrators understand academic fields is an important task for information scientists. Given the importance of interdisciplinary research, it is essential to be aware of disciplinary differences in aspects of scholarship, such as the significance of recent changes in a field. This paper identifies potential changes in 25 subject categories through a term comparison of words in article titles, keywords and abstracts in 1 year compared to the previous 4 years. The scholarly influence of new research issues is indirectly assessed with a citation analysis of articles matching each trending term. While topic-related words dominate the top terms, style, national focus, and language changes are also evident. Thus, as reflected in Scopus, fields evolve along multiple dimensions. Moreover, while articles exploiting new issues are usually more cited in some fields, such as Organic Chemistry, they are usually less cited in others, including History. The possible causes of new issues being less cited include externally driven temporary factors, such as disease outbreaks, and internally driven temporary decisions, such as a deliberate emphasis on a single topic (e.g., through a journal special issue).

0.016854495 = product of:
  0.03370899 = sum of:
    0.03370899 = product of:
      0.06741798 = sum of:
        0.06741798 = weight(_text_:e.g in 947) [ClassicSimilarity], result of:
          0.06741798 = score(doc=947,freq=2.0), product of:
            0.23393378 = queryWeight, product of:
              5.2168427 = idf(docFreq=651, maxDocs=44218)
              0.044842023 = queryNorm
            0.28819257 = fieldWeight in 947, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              5.2168427 = idf(docFreq=651, maxDocs=44218)
              0.0390625 = fieldNorm(doc=947)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Altmetrics are web-based quantitative impact or attention indicators for academic articles that have been proposed to supplement citation counts. This article reports the first assessment of the extent to which mature altmetrics from Altmetric.com and Mendeley associate with individual article quality scores. It exploits expert norm-referenced peer review scores from the UK Research Excellence Framework 2021 for 67,030+ journal articles in all fields 2014-2017/2018, split into 34 broadly field-based Units of Assessment (UoAs). Altmetrics correlated more strongly with research quality than previously found, although less strongly than raw and field normalized Scopus citation counts. Surprisingly, field normalizing citation counts can reduce their strength as a quality indicator for articles in a single field. For most UoAs, Mendeley reader counts are the best altmetric (e.g., three Spearman correlations with quality scores above 0.5), tweet counts are also a moderate strength indicator in eight UoAs (Spearman correlations with quality scores above 0.3), ahead of news (eight correlations above 0.3, but generally weaker), blogs (five correlations above 0.3), and Facebook (three correlations above 0.3) citations, at least in the United Kingdom. In general, altmetrics are the strongest indicators of research quality in the health and physical sciences and weakest in the arts and humanities.

0.01215095 = product of:
  0.0243019 = sum of:
    0.0243019 = product of:
      0.0486038 = sum of:
        0.0486038 = weight(_text_:22 in 77) [ClassicSimilarity], result of:
          0.0486038 = score(doc=77,freq=2.0), product of:
            0.15702912 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.044842023 = queryNorm
            0.30952093 = fieldWeight in 77, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0625 = fieldNorm(doc=77)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Date

4.12.2006 12:12:22

0.010740024 = product of:
  0.021480048 = sum of:
    0.021480048 = product of:
      0.042960096 = sum of:
        0.042960096 = weight(_text_:22 in 2734) [ClassicSimilarity], result of:
          0.042960096 = score(doc=2734,freq=4.0), product of:
            0.15702912 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.044842023 = 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)
  0.5 = coord(1/2)

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

0.009113212 = product of:
  0.018226424 = sum of:
    0.018226424 = product of:
      0.03645285 = sum of:
        0.03645285 = weight(_text_:22 in 2856) [ClassicSimilarity], result of:
          0.03645285 = score(doc=2856,freq=2.0), product of:
            0.15702912 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.044842023 = 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

0.009113212 = product of:
  0.018226424 = sum of:
    0.018226424 = product of:
      0.03645285 = sum of:
        0.03645285 = weight(_text_:22 in 3211) [ClassicSimilarity], result of:
          0.03645285 = score(doc=3211,freq=2.0), product of:
            0.15702912 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.044842023 = 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

0.009113212 = product of:
  0.018226424 = sum of:
    0.018226424 = product of:
      0.03645285 = sum of:
        0.03645285 = weight(_text_:22 in 4291) [ClassicSimilarity], result of:
          0.03645285 = score(doc=4291,freq=2.0), product of:
            0.15702912 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.044842023 = 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

0.0075943437 = product of:
  0.0151886875 = sum of:
    0.0151886875 = product of:
      0.030377375 = sum of:
        0.030377375 = weight(_text_:22 in 586) [ClassicSimilarity], result of:
          0.030377375 = score(doc=586,freq=2.0), product of:
            0.15702912 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.044842023 = 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)
  0.5 = coord(1/2)

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.

0.0075943437 = product of:
  0.0151886875 = sum of:
    0.0151886875 = product of:
      0.030377375 = sum of:
        0.030377375 = weight(_text_:22 in 57) [ClassicSimilarity], result of:
          0.030377375 = score(doc=57,freq=2.0), product of:
            0.15702912 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.044842023 = 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

0.0075943437 = product of:
  0.0151886875 = sum of:
    0.0151886875 = product of:
      0.030377375 = sum of:
        0.030377375 = weight(_text_:22 in 3806) [ClassicSimilarity], result of:
          0.030377375 = score(doc=3806,freq=2.0), product of:
            0.15702912 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.044842023 = 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

0.0075943437 = product of:
  0.0151886875 = sum of:
    0.0151886875 = product of:
      0.030377375 = sum of:
        0.030377375 = weight(_text_:22 in 178) [ClassicSimilarity], result of:
          0.030377375 = score(doc=178,freq=2.0), product of:
            0.15702912 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.044842023 = 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)
  0.5 = coord(1/2)

Date

20. 1.2015 18:30:22

0.0075943437 = product of:
  0.0151886875 = sum of:
    0.0151886875 = product of:
      0.030377375 = sum of:
        0.030377375 = weight(_text_:22 in 995) [ClassicSimilarity], result of:
          0.030377375 = score(doc=995,freq=2.0), product of:
            0.15702912 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.044842023 = queryNorm
            0.19345059 = fieldWeight in 995, 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=995)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Date

22. 6.2023 18:11:50