Search (27 results, page 1 of 2)

  • × author_ss:"Thelwall, M."
  1. Thelwall, M.; Buckley, K.; Paltoglou, G.; Cai, D.; Kappas, A.: Sentiment strength detection in short informal text (2010) 0.00
    0.0034957787 = product of:
      0.02796623 = sum of:
        0.02796623 = product of:
          0.041949343 = sum of:
            0.021069437 = weight(_text_:29 in 4200) [ClassicSimilarity], result of:
              0.021069437 = score(doc=4200,freq=2.0), product of:
                0.108422816 = queryWeight, product of:
                  3.5176873 = idf(docFreq=3565, maxDocs=44218)
                  0.030822188 = queryNorm
                0.19432661 = fieldWeight in 4200, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5176873 = idf(docFreq=3565, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=4200)
            0.020879906 = weight(_text_:22 in 4200) [ClassicSimilarity], result of:
              0.020879906 = score(doc=4200,freq=2.0), product of:
                0.10793405 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.030822188 = queryNorm
                0.19345059 = fieldWeight in 4200, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=4200)
          0.6666667 = coord(2/3)
      0.125 = coord(1/8)
    
    Date
    22. 1.2011 14:29:23
  2. Thelwall, M.; Thelwall, S.: ¬A thematic analysis of highly retweeted early COVID-19 tweets : consensus, information, dissent and lockdown life (2020) 0.00
    0.0034957787 = product of:
      0.02796623 = sum of:
        0.02796623 = product of:
          0.041949343 = sum of:
            0.021069437 = weight(_text_:29 in 178) [ClassicSimilarity], result of:
              0.021069437 = score(doc=178,freq=2.0), product of:
                0.108422816 = queryWeight, product of:
                  3.5176873 = idf(docFreq=3565, maxDocs=44218)
                  0.030822188 = queryNorm
                0.19432661 = fieldWeight in 178, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5176873 = idf(docFreq=3565, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=178)
            0.020879906 = weight(_text_:22 in 178) [ClassicSimilarity], result of:
              0.020879906 = score(doc=178,freq=2.0), product of:
                0.10793405 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.030822188 = 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)
          0.6666667 = coord(2/3)
      0.125 = coord(1/8)
    
    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
  3. Orduna-Malea, E.; Thelwall, M.; Kousha, K.: Web citations in patents : evidence of technological impact? (2017) 0.00
    0.0015337638 = product of:
      0.012270111 = sum of:
        0.012270111 = product of:
          0.03681033 = sum of:
            0.03681033 = weight(_text_:problem in 3764) [ClassicSimilarity], result of:
              0.03681033 = score(doc=3764,freq=2.0), product of:
                0.13082431 = queryWeight, product of:
                  4.244485 = idf(docFreq=1723, maxDocs=44218)
                  0.030822188 = queryNorm
                0.28137225 = fieldWeight in 3764, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  4.244485 = idf(docFreq=1723, maxDocs=44218)
                  0.046875 = fieldNorm(doc=3764)
          0.33333334 = coord(1/3)
      0.125 = coord(1/8)
    
    Abstract
    Patents sometimes cite webpages either as general background to the problem being addressed or to identify prior publications that limit the scope of the patent granted. Counts of the number of patents citing an organization's website may therefore provide an indicator of its technological capacity or relevance. This article introduces methods to extract URL citations from patents and evaluates the usefulness of counts of patent web citations as a technology indicator. An analysis of patents citing 200 US universities or 177 UK universities found computer science and engineering departments to be frequently cited, as well as research-related webpages, such as Wikipedia, YouTube, or the Internet Archive. Overall, however, patent URL citations seem to be frequent enough to be useful for ranking major US and the top few UK universities if popular hosted subdomains are filtered out, but the hit count estimates on the first search engine results page should not be relied upon for accuracy.
  4. Thelwall, M.; Ruschenburg, T.: Grundlagen und Forschungsfelder der Webometrie (2006) 0.00
    0.0013919937 = product of:
      0.01113595 = sum of:
        0.01113595 = product of:
          0.03340785 = sum of:
            0.03340785 = weight(_text_:22 in 77) [ClassicSimilarity], result of:
              0.03340785 = score(doc=77,freq=2.0), product of:
                0.10793405 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.030822188 = 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)
          0.33333334 = coord(1/3)
      0.125 = coord(1/8)
    
    Date
    4.12.2006 12:12:22
  5. Thelwall, M.; Vaughan, L.; Björneborn, L.: Webometrics (2004) 0.00
    0.0012781365 = product of:
      0.010225092 = sum of:
        0.010225092 = product of:
          0.030675275 = sum of:
            0.030675275 = weight(_text_:problem in 4279) [ClassicSimilarity], result of:
              0.030675275 = score(doc=4279,freq=2.0), product of:
                0.13082431 = queryWeight, product of:
                  4.244485 = idf(docFreq=1723, maxDocs=44218)
                  0.030822188 = queryNorm
                0.23447686 = fieldWeight in 4279, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  4.244485 = idf(docFreq=1723, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=4279)
          0.33333334 = coord(1/3)
      0.125 = coord(1/8)
    
    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.
  6. Thelwall, M.: Results from a web impact factor crawler (2001) 0.00
    0.0012781365 = product of:
      0.010225092 = sum of:
        0.010225092 = product of:
          0.030675275 = sum of:
            0.030675275 = weight(_text_:problem in 4490) [ClassicSimilarity], result of:
              0.030675275 = score(doc=4490,freq=2.0), product of:
                0.13082431 = queryWeight, product of:
                  4.244485 = idf(docFreq=1723, maxDocs=44218)
                  0.030822188 = queryNorm
                0.23447686 = fieldWeight in 4490, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  4.244485 = idf(docFreq=1723, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=4490)
          0.33333334 = coord(1/3)
      0.125 = coord(1/8)
    
    Abstract
    Web impact factors, the proposed web equivalent of impact factors for journals, can be calculated by using search engines. It has been found that the results are problematic because of the variable coverage of search engines as well as their ability to give significantly different results over short periods of time. The fundamental problem is that although some search engines provide a functionality that is capable of being used for impact calculations, this is not their primary task and therefore they do not give guarantees as to performance in this respect. In this paper, a bespoke web crawler designed specifically for the calculation of reliable WIFs is presented. This crawler was used to calculate WIFs for a number of UK universities, and the results of these calculations are discussed. The principal findings were that with certain restrictions, WIFs can be calculated reliably, but do not correlate with accepted research rankings owing to the variety of material hosted on university servers. Changes to the calculations to improve the fit of the results to research rankings are proposed, but there are still inherent problems undermining the reliability of the calculation. These problems still apply if the WIF scores are taken on their own as indicators of the general impact of any area of the Internet, but with care would not apply to online journals.
  7. Kousha, K.; Thelwall, M.: Patent citation analysis with Google (2017) 0.00
    0.0012781365 = product of:
      0.010225092 = sum of:
        0.010225092 = product of:
          0.030675275 = sum of:
            0.030675275 = weight(_text_:problem in 3317) [ClassicSimilarity], result of:
              0.030675275 = score(doc=3317,freq=2.0), product of:
                0.13082431 = queryWeight, product of:
                  4.244485 = idf(docFreq=1723, maxDocs=44218)
                  0.030822188 = queryNorm
                0.23447686 = fieldWeight in 3317, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  4.244485 = idf(docFreq=1723, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=3317)
          0.33333334 = coord(1/3)
      0.125 = coord(1/8)
    
    Abstract
    Citations from patents to scientific publications provide useful evidence about the commercial impact of academic research, but automatically searchable databases are needed to exploit this connection for large-scale patent citation evaluations. Google covers multiple different international patent office databases but does not index patent citations or allow automatic searches. In response, this article introduces a semiautomatic indirect method via Bing to extract and filter patent citations from Google to academic papers with an overall precision of 98%. The method was evaluated with 322,192 science and engineering Scopus articles from every second year for the period 1996-2012. Although manual Google Patent searches give more results, especially for articles with many patent citations, the difference is not large enough to be a major problem. Within Biomedical Engineering, Biotechnology, and Pharmacology & Pharmaceutics, 7% to 10% of Scopus articles had at least one patent citation but other fields had far fewer, so patent citation analysis is only relevant for a minority of publications. Low but positive correlations between Google Patent citations and Scopus citations across all fields suggest that traditional citation counts cannot substitute for patent citations when evaluating research.
  8. Levitt, J.M.; Thelwall, M.: Citation levels and collaboration within library and information science (2009) 0.00
    0.0012303602 = product of:
      0.009842882 = sum of:
        0.009842882 = product of:
          0.029528644 = sum of:
            0.029528644 = weight(_text_:22 in 2734) [ClassicSimilarity], result of:
              0.029528644 = score(doc=2734,freq=4.0), product of:
                0.10793405 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.030822188 = 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)
          0.33333334 = coord(1/3)
      0.125 = coord(1/8)
    
    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
  9. Thelwall, M.: Directing students to new information types : a new role for Google in literature searches? (2005) 0.00
    0.0012290506 = product of:
      0.009832405 = sum of:
        0.009832405 = product of:
          0.029497212 = sum of:
            0.029497212 = weight(_text_:29 in 364) [ClassicSimilarity], result of:
              0.029497212 = score(doc=364,freq=2.0), product of:
                0.108422816 = queryWeight, product of:
                  3.5176873 = idf(docFreq=3565, maxDocs=44218)
                  0.030822188 = queryNorm
                0.27205724 = fieldWeight in 364, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5176873 = idf(docFreq=3565, maxDocs=44218)
                  0.0546875 = fieldNorm(doc=364)
          0.33333334 = coord(1/3)
      0.125 = coord(1/8)
    
    Date
    3. 6.2007 16:37:29
  10. Vaughan, L.; Thelwall, M.: Search engine coverage bias : evidence and possible causes (2004) 0.00
    0.0010534719 = product of:
      0.008427775 = sum of:
        0.008427775 = product of:
          0.025283325 = sum of:
            0.025283325 = weight(_text_:29 in 2536) [ClassicSimilarity], result of:
              0.025283325 = score(doc=2536,freq=2.0), product of:
                0.108422816 = queryWeight, product of:
                  3.5176873 = idf(docFreq=3565, maxDocs=44218)
                  0.030822188 = queryNorm
                0.23319192 = fieldWeight in 2536, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5176873 = idf(docFreq=3565, maxDocs=44218)
                  0.046875 = fieldNorm(doc=2536)
          0.33333334 = coord(1/3)
      0.125 = coord(1/8)
    
    Date
    14. 8.2004 10:30:29
  11. Thelwall, M.; Kousha, K.: ResearchGate: Disseminating, communicating, and measuring scholarship? (2015) 0.00
    0.0010534719 = product of:
      0.008427775 = sum of:
        0.008427775 = product of:
          0.025283325 = sum of:
            0.025283325 = weight(_text_:29 in 1813) [ClassicSimilarity], result of:
              0.025283325 = score(doc=1813,freq=2.0), product of:
                0.108422816 = queryWeight, product of:
                  3.5176873 = idf(docFreq=3565, maxDocs=44218)
                  0.030822188 = queryNorm
                0.23319192 = fieldWeight in 1813, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5176873 = idf(docFreq=3565, maxDocs=44218)
                  0.046875 = fieldNorm(doc=1813)
          0.33333334 = coord(1/3)
      0.125 = coord(1/8)
    
    Date
    26. 4.2015 19:29:49
  12. Maflahi, N.; Thelwall, M.: When are readership counts as useful as citation counts? : Scopus versus Mendeley for LIS journals (2016) 0.00
    0.0010534719 = product of:
      0.008427775 = sum of:
        0.008427775 = product of:
          0.025283325 = sum of:
            0.025283325 = weight(_text_:29 in 2495) [ClassicSimilarity], result of:
              0.025283325 = score(doc=2495,freq=2.0), product of:
                0.108422816 = queryWeight, product of:
                  3.5176873 = idf(docFreq=3565, maxDocs=44218)
                  0.030822188 = queryNorm
                0.23319192 = fieldWeight in 2495, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5176873 = idf(docFreq=3565, maxDocs=44218)
                  0.046875 = fieldNorm(doc=2495)
          0.33333334 = coord(1/3)
      0.125 = coord(1/8)
    
    Date
    27.12.2015 11:29:37
  13. Thelwall, M.; Buckley, K.; Paltoglou, G.: Sentiment in Twitter events (2011) 0.00
    0.0010439953 = product of:
      0.008351962 = sum of:
        0.008351962 = product of:
          0.025055885 = sum of:
            0.025055885 = weight(_text_:22 in 4345) [ClassicSimilarity], result of:
              0.025055885 = score(doc=4345,freq=2.0), product of:
                0.10793405 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.030822188 = queryNorm
                0.23214069 = fieldWeight in 4345, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.046875 = fieldNorm(doc=4345)
          0.33333334 = coord(1/3)
      0.125 = coord(1/8)
    
    Date
    22. 1.2011 14:27:06
  14. Thelwall, M.; Maflahi, N.: Guideline references and academic citations as evidence of the clinical value of health research (2016) 0.00
    0.0010439953 = product of:
      0.008351962 = sum of:
        0.008351962 = product of:
          0.025055885 = sum of:
            0.025055885 = weight(_text_:22 in 2856) [ClassicSimilarity], result of:
              0.025055885 = score(doc=2856,freq=2.0), product of:
                0.10793405 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.030822188 = 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)
          0.33333334 = coord(1/3)
      0.125 = coord(1/8)
    
    Date
    19. 3.2016 12:22:00
  15. Thelwall, M.; Sud, P.: Mendeley readership counts : an investigation of temporal and disciplinary differences (2016) 0.00
    0.0010439953 = product of:
      0.008351962 = sum of:
        0.008351962 = product of:
          0.025055885 = sum of:
            0.025055885 = weight(_text_:22 in 3211) [ClassicSimilarity], result of:
              0.025055885 = score(doc=3211,freq=2.0), product of:
                0.10793405 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.030822188 = 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)
          0.33333334 = coord(1/3)
      0.125 = coord(1/8)
    
    Date
    16.11.2016 11:07:22
  16. Didegah, F.; Thelwall, M.: Co-saved, co-tweeted, and co-cited networks (2018) 0.00
    0.0010439953 = product of:
      0.008351962 = sum of:
        0.008351962 = product of:
          0.025055885 = sum of:
            0.025055885 = weight(_text_:22 in 4291) [ClassicSimilarity], result of:
              0.025055885 = score(doc=4291,freq=2.0), product of:
                0.10793405 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.030822188 = 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)
          0.33333334 = coord(1/3)
      0.125 = coord(1/8)
    
    Date
    28. 7.2018 10:00:22
  17. Vaughan, L.; Thelwall, M.: Scholarly use of the Web : what are the key inducers of links to journal Web sites? (2003) 0.00
    8.7789324E-4 = product of:
      0.007023146 = sum of:
        0.007023146 = product of:
          0.021069437 = sum of:
            0.021069437 = weight(_text_:29 in 1236) [ClassicSimilarity], result of:
              0.021069437 = score(doc=1236,freq=2.0), product of:
                0.108422816 = queryWeight, product of:
                  3.5176873 = idf(docFreq=3565, maxDocs=44218)
                  0.030822188 = queryNorm
                0.19432661 = fieldWeight in 1236, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5176873 = idf(docFreq=3565, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=1236)
          0.33333334 = coord(1/3)
      0.125 = coord(1/8)
    
    Source
    Journal of the American Society for Information Science and technology. 54(2003) no.1, S.29-38
  18. Thelwall, M.; Prabowo, R.; Fairclough, R.: Are raw RSS feeds suitable for broad issue scanning? : a science concern case study (2006) 0.00
    8.7789324E-4 = product of:
      0.007023146 = sum of:
        0.007023146 = product of:
          0.021069437 = sum of:
            0.021069437 = weight(_text_:29 in 6116) [ClassicSimilarity], result of:
              0.021069437 = score(doc=6116,freq=2.0), product of:
                0.108422816 = queryWeight, product of:
                  3.5176873 = idf(docFreq=3565, maxDocs=44218)
                  0.030822188 = queryNorm
                0.19432661 = fieldWeight in 6116, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5176873 = idf(docFreq=3565, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=6116)
          0.33333334 = coord(1/3)
      0.125 = coord(1/8)
    
    Date
    21.10.2006 19:29:49
  19. Levitt, J.M.; Thelwall, M.; Oppenheim, C.: Variations between subjects in the extent to which the social sciences have become more interdisciplinary (2011) 0.00
    8.7789324E-4 = product of:
      0.007023146 = sum of:
        0.007023146 = product of:
          0.021069437 = sum of:
            0.021069437 = weight(_text_:29 in 4465) [ClassicSimilarity], result of:
              0.021069437 = score(doc=4465,freq=2.0), product of:
                0.108422816 = queryWeight, product of:
                  3.5176873 = idf(docFreq=3565, maxDocs=44218)
                  0.030822188 = queryNorm
                0.19432661 = fieldWeight in 4465, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5176873 = idf(docFreq=3565, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=4465)
          0.33333334 = coord(1/3)
      0.125 = coord(1/8)
    
    Date
    4. 7.2011 19:39:29
  20. Thelwall, M.; Sud, P.; Vis, F.: Commenting on YouTube videos : From guatemalan rock to El Big Bang (2012) 0.00
    8.7789324E-4 = product of:
      0.007023146 = sum of:
        0.007023146 = product of:
          0.021069437 = sum of:
            0.021069437 = weight(_text_:29 in 63) [ClassicSimilarity], result of:
              0.021069437 = score(doc=63,freq=2.0), product of:
                0.108422816 = queryWeight, product of:
                  3.5176873 = idf(docFreq=3565, maxDocs=44218)
                  0.030822188 = queryNorm
                0.19432661 = fieldWeight in 63, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5176873 = idf(docFreq=3565, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=63)
          0.33333334 = coord(1/3)
      0.125 = coord(1/8)
    
    Abstract
    YouTube is one of the world's most popular websites and hosts numerous amateur and professional videos. Comments on these videos might be researched to give insights into audience reactions to important issues or particular videos. Yet, little is known about YouTube discussions in general: how frequent they are, who typically participates, and the role of sentiment. This article fills this gap through an analysis of large samples of text comments on YouTube videos. The results identify patterns and give some benchmarks against which future YouTube research into individual videos can be compared. For instance, the typical YouTube comment was mildly positive, was posted by a 29-year-old male, and contained 58 characters. About 23% of comments in the complete comment sets were replies to previous comments. There was no typical density of discussion on YouTube videos in the sense of the proportion of replies to other comments: videos with both few and many replies were common. The YouTube audience engaged with each other disproportionately when making negative comments, however; positive comments elicited few replies. The biggest trigger of discussion seemed to be religion, whereas the videos attracting the least discussion were predominantly from the Music, Comedy, and How to & Style categories. This suggests different audience uses for YouTube, from passive entertainment to active debating.