Search (48 results, page 1 of 3)

  • × author_ss:"Thelwall, M."
  1. Maflahi, N.; Thelwall, M.: When are readership counts as useful as citation counts? : Scopus versus Mendeley for LIS journals (2016) 0.02
    0.01861422 = product of:
      0.10703176 = sum of:
        0.015522547 = product of:
          0.031045094 = sum of:
            0.031045094 = weight(_text_:bibliothekswesen in 2495) [ClassicSimilarity], result of:
              0.031045094 = score(doc=2495,freq=2.0), product of:
                0.10505787 = queryWeight, product of:
                  4.457672 = idf(docFreq=1392, maxDocs=44218)
                  0.023567878 = queryNorm
                0.2955047 = fieldWeight in 2495, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  4.457672 = idf(docFreq=1392, maxDocs=44218)
                  0.046875 = fieldNorm(doc=2495)
          0.5 = coord(1/2)
        0.031703662 = weight(_text_:informationswissenschaft in 2495) [ClassicSimilarity], result of:
          0.031703662 = score(doc=2495,freq=2.0), product of:
            0.10616633 = queryWeight, product of:
              4.504705 = idf(docFreq=1328, maxDocs=44218)
              0.023567878 = queryNorm
            0.29862255 = fieldWeight in 2495, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.504705 = idf(docFreq=1328, maxDocs=44218)
              0.046875 = fieldNorm(doc=2495)
        0.031045094 = weight(_text_:bibliothekswesen in 2495) [ClassicSimilarity], result of:
          0.031045094 = score(doc=2495,freq=2.0), product of:
            0.10505787 = queryWeight, product of:
              4.457672 = idf(docFreq=1392, maxDocs=44218)
              0.023567878 = queryNorm
            0.2955047 = fieldWeight in 2495, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.457672 = idf(docFreq=1392, maxDocs=44218)
              0.046875 = fieldNorm(doc=2495)
        0.028760463 = sum of:
          0.0094278185 = weight(_text_:1 in 2495) [ClassicSimilarity], result of:
            0.0094278185 = score(doc=2495,freq=2.0), product of:
              0.057894554 = queryWeight, product of:
                2.4565027 = idf(docFreq=10304, maxDocs=44218)
                0.023567878 = queryNorm
              0.16284466 = fieldWeight in 2495, product of:
                1.4142135 = tf(freq=2.0), with freq of:
                  2.0 = termFreq=2.0
                2.4565027 = idf(docFreq=10304, maxDocs=44218)
                0.046875 = fieldNorm(doc=2495)
          0.019332644 = weight(_text_:29 in 2495) [ClassicSimilarity], result of:
            0.019332644 = score(doc=2495,freq=2.0), product of:
              0.08290443 = queryWeight, product of:
                3.5176873 = idf(docFreq=3565, maxDocs=44218)
                0.023567878 = 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)
      0.17391305 = coord(4/23)
    
    Date
    27.12.2015 11:29:37
    Field
    Bibliothekswesen
    Informationswissenschaft
    Source
    Journal of the Association for Information Science and Technology. 67(2016) no.1, S.191-199
  2. Thelwall, M.; Ruschenburg, T.: Grundlagen und Forschungsfelder der Webometrie (2006) 0.02
    0.015550195 = product of:
      0.08941362 = sum of:
        0.017723909 = weight(_text_:und in 77) [ClassicSimilarity], result of:
          0.017723909 = score(doc=77,freq=6.0), product of:
            0.052235067 = queryWeight, product of:
              2.216367 = idf(docFreq=13101, maxDocs=44218)
              0.023567878 = queryNorm
            0.33931053 = fieldWeight in 77, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              2.216367 = idf(docFreq=13101, maxDocs=44218)
              0.0625 = fieldNorm(doc=77)
        0.04227155 = weight(_text_:informationswissenschaft in 77) [ClassicSimilarity], result of:
          0.04227155 = score(doc=77,freq=2.0), product of:
            0.10616633 = queryWeight, product of:
              4.504705 = idf(docFreq=1328, maxDocs=44218)
              0.023567878 = queryNorm
            0.3981634 = fieldWeight in 77, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.504705 = idf(docFreq=1328, maxDocs=44218)
              0.0625 = fieldNorm(doc=77)
        0.016645677 = weight(_text_:im in 77) [ClassicSimilarity], result of:
          0.016645677 = score(doc=77,freq=2.0), product of:
            0.066621356 = queryWeight, product of:
              2.8267863 = idf(docFreq=7115, maxDocs=44218)
              0.023567878 = queryNorm
            0.24985497 = fieldWeight in 77, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.8267863 = idf(docFreq=7115, maxDocs=44218)
              0.0625 = fieldNorm(doc=77)
        0.012772488 = product of:
          0.025544977 = sum of:
            0.025544977 = weight(_text_:22 in 77) [ClassicSimilarity], result of:
              0.025544977 = score(doc=77,freq=2.0), product of:
                0.08253069 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.023567878 = 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)
      0.17391305 = coord(4/23)
    
    Abstract
    Die Webometrie ist ein Teilbereich der Informationswissenschaft der zur Zeit auf die Analyse von Linkstrukturen konzentriert ist. Er ist stark von der Zitationsanalyse geprägt, wie der empirische Schwerpunkt auf der Wissenschaftsanalyse zeigt. In diesem Beitrag diskutieren wir die Nutzung linkbasierter Maße in einem breiten informetrischen Kontext und bewerten verschiedene Verfahren, auch im Hinblick auf ihr generelles Potentialfür die Sozialwissenschaften. Dabei wird auch ein allgemeiner Rahmenfür Linkanalysen mit den erforderlichen Arbeitsschritten vorgestellt. Abschließend werden vielversprechende zukünftige Anwendungsfelder der Webometrie benannt, unter besonderer Berücksichtigung der Analyse von Blogs.
    Date
    4.12.2006 12:12:22
    Source
    Information - Wissenschaft und Praxis. 57(2006) H.8, S.401-406
  3. Levitt, J.M.; Thelwall, M.: Citation levels and collaboration within library and information science (2009) 0.01
    0.013307041 = product of:
      0.07651548 = sum of:
        0.012935456 = product of:
          0.025870912 = sum of:
            0.025870912 = weight(_text_:bibliothekswesen in 2734) [ClassicSimilarity], result of:
              0.025870912 = score(doc=2734,freq=2.0), product of:
                0.10505787 = queryWeight, product of:
                  4.457672 = idf(docFreq=1392, maxDocs=44218)
                  0.023567878 = queryNorm
                0.24625391 = fieldWeight in 2734, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  4.457672 = idf(docFreq=1392, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=2734)
          0.5 = coord(1/2)
        0.026419718 = weight(_text_:informationswissenschaft in 2734) [ClassicSimilarity], result of:
          0.026419718 = score(doc=2734,freq=2.0), product of:
            0.10616633 = queryWeight, product of:
              4.504705 = idf(docFreq=1328, maxDocs=44218)
              0.023567878 = queryNorm
            0.24885213 = fieldWeight in 2734, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.504705 = idf(docFreq=1328, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2734)
        0.025870912 = weight(_text_:bibliothekswesen in 2734) [ClassicSimilarity], result of:
          0.025870912 = score(doc=2734,freq=2.0), product of:
            0.10505787 = queryWeight, product of:
              4.457672 = idf(docFreq=1392, maxDocs=44218)
              0.023567878 = queryNorm
            0.24625391 = fieldWeight in 2734, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              4.457672 = idf(docFreq=1392, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2734)
        0.011289392 = product of:
          0.022578783 = sum of:
            0.022578783 = weight(_text_:22 in 2734) [ClassicSimilarity], result of:
              0.022578783 = score(doc=2734,freq=4.0), product of:
                0.08253069 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.023567878 = 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)
      0.17391305 = coord(4/23)
    
    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
    Field
    Bibliothekswesen
    Informationswissenschaft
  4. Thelwall, M.; Buckley, K.; Paltoglou, G.; Cai, D.; Kappas, A.: Sentiment strength detection in short informal text (2010) 0.00
    0.0027782484 = product of:
      0.031949855 = sum of:
        0.02396705 = sum of:
          0.007856515 = weight(_text_:1 in 4200) [ClassicSimilarity], result of:
            0.007856515 = score(doc=4200,freq=2.0), product of:
              0.057894554 = queryWeight, product of:
                2.4565027 = idf(docFreq=10304, maxDocs=44218)
                0.023567878 = queryNorm
              0.13570388 = fieldWeight in 4200, product of:
                1.4142135 = tf(freq=2.0), with freq of:
                  2.0 = termFreq=2.0
                2.4565027 = idf(docFreq=10304, maxDocs=44218)
                0.0390625 = fieldNorm(doc=4200)
          0.016110536 = weight(_text_:29 in 4200) [ClassicSimilarity], result of:
            0.016110536 = score(doc=4200,freq=2.0), product of:
              0.08290443 = queryWeight, product of:
                3.5176873 = idf(docFreq=3565, maxDocs=44218)
                0.023567878 = 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)
        0.007982805 = product of:
          0.01596561 = sum of:
            0.01596561 = weight(_text_:22 in 4200) [ClassicSimilarity], result of:
              0.01596561 = score(doc=4200,freq=2.0), product of:
                0.08253069 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.023567878 = queryNorm
                0.19345059 = fieldWeight in 4200, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=4200)
          0.5 = coord(1/2)
      0.08695652 = coord(2/23)
    
    Abstract
    A huge number of informal messages are posted every day in social network sites, blogs, and discussion forums. Emotions seem to be frequently important in these texts for expressing friendship, showing social support or as part of online arguments. Algorithms to identify sentiment and sentiment strength are needed to help understand the role of emotion in this informal communication and also to identify inappropriate or anomalous affective utterances, potentially associated with threatening behavior to the self or others. Nevertheless, existing sentiment detection algorithms tend to be commercially oriented, designed to identify opinions about products rather than user behaviors. This article partly fills this gap with a new algorithm, SentiStrength, to extract sentiment strength from informal English text, using new methods to exploit the de facto grammars and spelling styles of cyberspace. Applied to MySpace comments and with a lookup table of term sentiment strengths optimized by machine learning, SentiStrength is able to predict positive emotion with 60.6% accuracy and negative emotion with 72.8% accuracy, both based upon strength scales of 1-5. The former, but not the latter, is better than baseline and a wide range of general machine learning approaches.
    Date
    22. 1.2011 14:29:23
  5. Vaughan, L.; Thelwall, M.: Search engine coverage bias : evidence and possible causes (2004) 0.00
    0.0015964593 = product of:
      0.018359281 = sum of:
        0.009666322 = product of:
          0.019332644 = sum of:
            0.019332644 = weight(_text_:29 in 2536) [ClassicSimilarity], result of:
              0.019332644 = score(doc=2536,freq=2.0), product of:
                0.08290443 = queryWeight, product of:
                  3.5176873 = idf(docFreq=3565, maxDocs=44218)
                  0.023567878 = 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)
          0.5 = coord(1/2)
        0.008692958 = product of:
          0.017385917 = sum of:
            0.017385917 = weight(_text_:international in 2536) [ClassicSimilarity], result of:
              0.017385917 = score(doc=2536,freq=2.0), product of:
                0.078619614 = queryWeight, product of:
                  3.33588 = idf(docFreq=4276, maxDocs=44218)
                  0.023567878 = queryNorm
                0.22113968 = fieldWeight in 2536, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.33588 = idf(docFreq=4276, maxDocs=44218)
                  0.046875 = fieldNorm(doc=2536)
          0.5 = coord(1/2)
      0.08695652 = coord(2/23)
    
    Abstract
    Commercial search engines are now playing an increasingly important role in Web information dissemination and access. Of particular interest to business and national governments is whether the big engines have coverage biased towards the US or other countries. In our study we tested for national biases in three major search engines and found significant differences in their coverage of commercial Web sites. The US sites were much better covered than the others in the study: sites from China, Taiwan and Singapore. We then examined the possible technical causes of the differences and found that the language of a site does not affect its coverage by search engines. However, the visibility of a site, measured by the number of links to it, affects its chance to be covered by search engines. We conclude that the coverage bias does exist but this is due not to deliberate choices of the search engines but occurs as a natural result of cumulative advantage effects of US sites on the Web. Nevertheless, the bias remains a cause for international concern.
    Date
    14. 8.2004 10:30:29
  6. Thelwall, M.; Li, X.; Barjak, F.; Robinson, S.: Assessing the international web connectivity of research groups (2008) 0.00
    0.001432649 = product of:
      0.016475463 = sum of:
        0.0039282576 = product of:
          0.007856515 = sum of:
            0.007856515 = weight(_text_:1 in 1401) [ClassicSimilarity], result of:
              0.007856515 = score(doc=1401,freq=2.0), product of:
                0.057894554 = queryWeight, product of:
                  2.4565027 = idf(docFreq=10304, maxDocs=44218)
                  0.023567878 = queryNorm
                0.13570388 = fieldWeight in 1401, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  2.4565027 = idf(docFreq=10304, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=1401)
          0.5 = coord(1/2)
        0.012547206 = product of:
          0.025094412 = sum of:
            0.025094412 = weight(_text_:international in 1401) [ClassicSimilarity], result of:
              0.025094412 = score(doc=1401,freq=6.0), product of:
                0.078619614 = queryWeight, product of:
                  3.33588 = idf(docFreq=4276, maxDocs=44218)
                  0.023567878 = queryNorm
                0.31918767 = fieldWeight in 1401, product of:
                  2.4494898 = tf(freq=6.0), with freq of:
                    6.0 = termFreq=6.0
                  3.33588 = idf(docFreq=4276, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=1401)
          0.5 = coord(1/2)
      0.08695652 = coord(2/23)
    
    Abstract
    Purpose - The purpose of this paper is to claim that it is useful to assess the web connectivity of research groups, describe hyperlink-based techniques to achieve this and present brief details of European life sciences research groups as a case study. Design/methodology/approach - A commercial search engine was harnessed to deliver hyperlink data via its automatic query submission interface. A special purpose link analysis tool, LexiURL, then summarised and graphed the link data in appropriate ways. Findings - Webometrics can provide a wide range of descriptive information about the international connectivity of research groups. Research limitations/implications - Only one field was analysed, data was taken from only one search engine, and the results were not validated. Practical implications - Web connectivity seems to be particularly important for attracting overseas job applicants and to promote research achievements and capabilities, and hence we contend that it can be useful for national and international governments to use webometrics to ensure that the web is being used effectively by research groups. Originality/value - This is the first paper to make a case for the value of using a range of webometric techniques to evaluate the web presences of research groups within a field, and possibly the first "applied" webometrics study produced for an external contract.
    Source
    Aslib proceedings. 60(2008) no.1, S.18-31
  7. Thelwall, M.; Thelwall, S.: ¬A thematic analysis of highly retweeted early COVID-19 tweets : consensus, information, dissent and lockdown life (2020) 0.00
    0.001394615 = product of:
      0.016038073 = sum of:
        0.008055268 = product of:
          0.016110536 = sum of:
            0.016110536 = weight(_text_:29 in 178) [ClassicSimilarity], result of:
              0.016110536 = score(doc=178,freq=2.0), product of:
                0.08290443 = queryWeight, product of:
                  3.5176873 = idf(docFreq=3565, maxDocs=44218)
                  0.023567878 = 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)
          0.5 = coord(1/2)
        0.007982805 = product of:
          0.01596561 = sum of:
            0.01596561 = weight(_text_:22 in 178) [ClassicSimilarity], result of:
              0.01596561 = score(doc=178,freq=2.0), product of:
                0.08253069 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.023567878 = 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)
      0.08695652 = coord(2/23)
    
    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
  8. Thelwall, M.; Buckley, K.; Paltoglou, G.: Sentiment in Twitter events (2011) 0.00
    0.0012428935 = product of:
      0.014293276 = sum of:
        0.0047139092 = product of:
          0.0094278185 = sum of:
            0.0094278185 = weight(_text_:1 in 4345) [ClassicSimilarity], result of:
              0.0094278185 = score(doc=4345,freq=2.0), product of:
                0.057894554 = queryWeight, product of:
                  2.4565027 = idf(docFreq=10304, maxDocs=44218)
                  0.023567878 = queryNorm
                0.16284466 = fieldWeight in 4345, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  2.4565027 = idf(docFreq=10304, maxDocs=44218)
                  0.046875 = fieldNorm(doc=4345)
          0.5 = coord(1/2)
        0.009579366 = product of:
          0.019158732 = sum of:
            0.019158732 = weight(_text_:22 in 4345) [ClassicSimilarity], result of:
              0.019158732 = score(doc=4345,freq=2.0), product of:
                0.08253069 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.023567878 = queryNorm
                0.23214069 = fieldWeight in 4345, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.046875 = fieldNorm(doc=4345)
          0.5 = coord(1/2)
      0.08695652 = coord(2/23)
    
    Abstract
    The microblogging site Twitter generates a constant stream of communication, some of which concerns events of general interest. An analysis of Twitter may, therefore, give insights into why particular events resonate with the population. This article reports a study of a month of English Twitter posts, assessing whether popular events are typically associated with increases in sentiment strength, as seems intuitively likely. Using the top 30 events, determined by a measure of relative increase in (general) term usage, the results give strong evidence that popular events are normally associated with increases in negative sentiment strength and some evidence that peaks of interest in events have stronger positive sentiment than the time before the peak. It seems that many positive events, such as the Oscars, are capable of generating increased negative sentiment in reaction to them. Nevertheless, the surprisingly small average change in sentiment associated with popular events (typically 1% and only 6% for Tiger Woods' confessions) is consistent with events affording posters opportunities to satisfy pre-existing personal goals more often than eliciting instinctive reactions.
    Date
    22. 1.2011 14:27:06
  9. Vaughan, L.; Thelwall, M.: Scholarly use of the Web : what are the key inducers of links to journal Web sites? (2003) 0.00
    0.0010420457 = product of:
      0.02396705 = sum of:
        0.02396705 = sum of:
          0.007856515 = weight(_text_:1 in 1236) [ClassicSimilarity], result of:
            0.007856515 = score(doc=1236,freq=2.0), product of:
              0.057894554 = queryWeight, product of:
                2.4565027 = idf(docFreq=10304, maxDocs=44218)
                0.023567878 = queryNorm
              0.13570388 = fieldWeight in 1236, product of:
                1.4142135 = tf(freq=2.0), with freq of:
                  2.0 = termFreq=2.0
                2.4565027 = idf(docFreq=10304, maxDocs=44218)
                0.0390625 = fieldNorm(doc=1236)
          0.016110536 = weight(_text_:29 in 1236) [ClassicSimilarity], result of:
            0.016110536 = score(doc=1236,freq=2.0), product of:
              0.08290443 = queryWeight, product of:
                3.5176873 = idf(docFreq=3565, maxDocs=44218)
                0.023567878 = 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)
      0.04347826 = coord(1/23)
    
    Source
    Journal of the American Society for Information Science and technology. 54(2003) no.1, S.29-38
  10. Kousha, K.; Thelwall, M.: Patent citation analysis with Google (2017) 0.00
    9.7151217E-4 = product of:
      0.01117239 = sum of:
        0.0039282576 = product of:
          0.007856515 = sum of:
            0.007856515 = weight(_text_:1 in 3317) [ClassicSimilarity], result of:
              0.007856515 = score(doc=3317,freq=2.0), product of:
                0.057894554 = queryWeight, product of:
                  2.4565027 = idf(docFreq=10304, maxDocs=44218)
                  0.023567878 = queryNorm
                0.13570388 = fieldWeight in 3317, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  2.4565027 = idf(docFreq=10304, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=3317)
          0.5 = coord(1/2)
        0.0072441325 = product of:
          0.014488265 = sum of:
            0.014488265 = weight(_text_:international in 3317) [ClassicSimilarity], result of:
              0.014488265 = score(doc=3317,freq=2.0), product of:
                0.078619614 = queryWeight, product of:
                  3.33588 = idf(docFreq=4276, maxDocs=44218)
                  0.023567878 = queryNorm
                0.18428308 = fieldWeight in 3317, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.33588 = idf(docFreq=4276, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=3317)
          0.5 = coord(1/2)
      0.08695652 = coord(2/23)
    
    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.
    Source
    Journal of the Association for Information Science and Technology. 68(2017) no.1, S.48-61
  11. Wilkinson, D.; Thelwall, M.: Trending Twitter topics in English : an international comparison (2012) 0.00
    8.333119E-4 = product of:
      0.019166173 = sum of:
        0.019166173 = product of:
          0.038332347 = sum of:
            0.038332347 = weight(_text_:international in 375) [ClassicSimilarity], result of:
              0.038332347 = score(doc=375,freq=14.0), product of:
                0.078619614 = queryWeight, product of:
                  3.33588 = idf(docFreq=4276, maxDocs=44218)
                  0.023567878 = queryNorm
                0.48756722 = fieldWeight in 375, product of:
                  3.7416575 = tf(freq=14.0), with freq of:
                    14.0 = termFreq=14.0
                  3.33588 = idf(docFreq=4276, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=375)
          0.5 = coord(1/2)
      0.04347826 = coord(1/23)
    
    Abstract
    The worldwide span of the microblogging service Twitter provides an opportunity to make international comparisons of trending topics of interest, such as news stories. Previous international comparisons of news interests have tended to use surveys and may bypass topics not well covered in the mainstream media. This study uses 9 months of English-language Tweets from the United Kingdom, United States, India, South Africa, New Zealand, and Australia. Based upon the top 50 trending keywords in each country from the 0.5 billion Tweets collected, festivals or religious events are the most common, followed by media events, politics, human interest, and sports. U.S. trending topics have the most interest in the other countries and Indian trending topics the least. Conversely, India is the most interested in other countries' trending topics and the United States the least. This gives evidence of an international hierarchy of perceived importance or relevance with some issues, such as the international interest in U.S. Thanksgiving celebrations, apparently not being directly driven by the media. This hierarchy echoes, and may be caused by, similar news coverage trends. Although the current imbalanced international news coverage does not seem to be out of step with public news interests, the political implication is that the Twitter-using public reflects, and hence seems to implicitly accept, international imbalances in news media agenda setting rather than combating them. This is an issue for those believing that these imbalances make the media too powerful.
  12. Thelwall, M.; Vann, K.; Fairclough, R.: Web issue analysis : an integrated water resource management case study (2006) 0.00
    6.546369E-4 = product of:
      0.015056648 = sum of:
        0.015056648 = product of:
          0.030113297 = sum of:
            0.030113297 = weight(_text_:international in 5906) [ClassicSimilarity], result of:
              0.030113297 = score(doc=5906,freq=6.0), product of:
                0.078619614 = queryWeight, product of:
                  3.33588 = idf(docFreq=4276, maxDocs=44218)
                  0.023567878 = queryNorm
                0.38302523 = fieldWeight in 5906, product of:
                  2.4494898 = tf(freq=6.0), with freq of:
                    6.0 = termFreq=6.0
                  3.33588 = idf(docFreq=4276, maxDocs=44218)
                  0.046875 = fieldNorm(doc=5906)
          0.5 = coord(1/2)
      0.04347826 = coord(1/23)
    
    Abstract
    In this article Web issue analysis is introduced as a new technique to investigate an issue as reflected on the Web. The issue chosen, integrated water resource management (IWRM), is a United Nations-initiated paradigm for managing water resources in an international context, particularly in developing nations. As with many international governmental initiatives, there is a considerable body of online information about it: 41.381 hypertext markup language (HTML) pages and 28.735 PDF documents mentioning the issue were downloaded. A page uniform resource locator (URL) and link analysis revealed the international and sectoral spread of IWRM. A noun and noun phrase occurrence analysis was used to identify the issues most commonly discussed, revealing some unexpected topics such as private sector and economic growth. Although the complexity of the methods required to produce meaningful statistics from the data is disadvantageous to easy interpretation, it was still possible to produce data that could be subject to a reasonably intuitive interpretation. Hence Web issue analysis is claimed to be a useful new technique for information science.
  13. Thelwall, M.; Maflahi, N.: Are scholarly articles disproportionately read in their own country? : An analysis of mendeley readers (2015) 0.00
    5.455307E-4 = product of:
      0.012547206 = sum of:
        0.012547206 = product of:
          0.025094412 = sum of:
            0.025094412 = weight(_text_:international in 1850) [ClassicSimilarity], result of:
              0.025094412 = score(doc=1850,freq=6.0), product of:
                0.078619614 = queryWeight, product of:
                  3.33588 = idf(docFreq=4276, maxDocs=44218)
                  0.023567878 = queryNorm
                0.31918767 = fieldWeight in 1850, product of:
                  2.4494898 = tf(freq=6.0), with freq of:
                    6.0 = termFreq=6.0
                  3.33588 = idf(docFreq=4276, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=1850)
          0.5 = coord(1/2)
      0.04347826 = coord(1/23)
    
    Abstract
    International collaboration tends to result in more highly cited research and, partly as a result of this, many research funding schemes are specifically international in scope. Nevertheless, it is not clear whether this citation advantage is the result of higher quality research or due to other factors, such as a larger audience for the publications. To test whether the apparent advantage of internationally collaborative research may be due to additional interest in articles from the countries of the authors, this article assesses the extent to which the national affiliations of the authors of articles affect the national affiliations of their Mendeley readers. Based on English-language Web of Science articles in 10 fields from science, medicine, social science, and the humanities, the results of statistical models comparing author and reader affiliations suggest that, in most fields, Mendeley users are disproportionately readers of articles authored from within their own country. In addition, there are several cases in which Mendeley users from certain countries tend to ignore articles from specific other countries, although it is not clear whether this reflects national biases or different national specialisms within a field. In conclusion, research funders should not incentivize international collaboration on the basis that it is, in general, higher quality because its higher impact may be primarily due to its larger audience. Moreover, authors should guard against national biases in their reading to select only the best and most relevant publications to inform their research.
  14. Thelwall, M.: Directing students to new information types : a new role for Google in literature searches? (2005) 0.00
    4.903207E-4 = product of:
      0.011277375 = sum of:
        0.011277375 = product of:
          0.02255475 = sum of:
            0.02255475 = weight(_text_:29 in 364) [ClassicSimilarity], result of:
              0.02255475 = score(doc=364,freq=2.0), product of:
                0.08290443 = queryWeight, product of:
                  3.5176873 = idf(docFreq=3565, maxDocs=44218)
                  0.023567878 = 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)
          0.5 = coord(1/2)
      0.04347826 = coord(1/23)
    
    Date
    3. 6.2007 16:37:29
  15. Sud, P.; Thelwall, M.: Not all international collaboration is beneficial : the Mendeley readership and citation impact of biochemical research collaboration (2016) 0.00
    4.3642457E-4 = product of:
      0.010037765 = sum of:
        0.010037765 = product of:
          0.02007553 = sum of:
            0.02007553 = weight(_text_:international in 3048) [ClassicSimilarity], result of:
              0.02007553 = score(doc=3048,freq=6.0), product of:
                0.078619614 = queryWeight, product of:
                  3.33588 = idf(docFreq=4276, maxDocs=44218)
                  0.023567878 = queryNorm
                0.25535014 = fieldWeight in 3048, product of:
                  2.4494898 = tf(freq=6.0), with freq of:
                    6.0 = termFreq=6.0
                  3.33588 = idf(docFreq=4276, maxDocs=44218)
                  0.03125 = fieldNorm(doc=3048)
          0.5 = coord(1/2)
      0.04347826 = coord(1/23)
    
    Abstract
    This study aims to identify the way researchers collaborate with other researchers in the course of the scientific research life cycle and provide information to the designers of e-Science and e-Research implementations. On the basis of in-depth interviews with and on-site observations of 24 scientists and a follow-up focus group interview in the field of bioscience/nanoscience and technology in Korea, we examined scientific collaboration using the framework of the scientific research life cycle. We attempt to explain the major motiBiochemistry is a highly funded research area that is typified by large research teams and is important for many areas of the life sciences. This article investigates the citation impact and Mendeley readership impact of biochemistry research from 2011 in the Web of Science according to the type of collaboration involved. Negative binomial regression models are used that incorporate, for the first time, the inclusion of specific countries within a team. The results show that, holding other factors constant, larger teams robustly associate with higher impact research, but including additional departments has no effect and adding extra institutions tends to reduce the impact of research. Although international collaboration is apparently not advantageous in general, collaboration with the United States, and perhaps also with some other countries, seems to increase impact. In contrast, collaborations with some other nations seems to decrease impact, although both findings could be due to factors such as differing national proportions of excellent researchers. As a methodological implication, simpler statistical models would find international collaboration to be generally beneficial and so it is important to take into account specific countries when examining collaboration.t only in the beginning phase of the cycle. For communication and information-sharing practices, scientists continue to favor traditional means of communication for security reasons. Barriers to collaboration throughout the phases included different priorities, competitive tensions, and a hierarchical culture among collaborators, whereas credit sharing was a barrier in the research product phase.
  16. Thelwall, M.; Kousha, K.: ResearchGate: Disseminating, communicating, and measuring scholarship? (2015) 0.00
    4.2027488E-4 = product of:
      0.009666322 = sum of:
        0.009666322 = product of:
          0.019332644 = sum of:
            0.019332644 = weight(_text_:29 in 1813) [ClassicSimilarity], result of:
              0.019332644 = score(doc=1813,freq=2.0), product of:
                0.08290443 = queryWeight, product of:
                  3.5176873 = idf(docFreq=3565, maxDocs=44218)
                  0.023567878 = 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)
          0.5 = coord(1/2)
      0.04347826 = coord(1/23)
    
    Date
    26. 4.2015 19:29:49
  17. Thelwall, M.; Maflahi, N.: Guideline references and academic citations as evidence of the clinical value of health research (2016) 0.00
    4.1649418E-4 = product of:
      0.009579366 = sum of:
        0.009579366 = product of:
          0.019158732 = sum of:
            0.019158732 = weight(_text_:22 in 2856) [ClassicSimilarity], result of:
              0.019158732 = score(doc=2856,freq=2.0), product of:
                0.08253069 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.023567878 = 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)
      0.04347826 = coord(1/23)
    
    Date
    19. 3.2016 12:22:00
  18. Thelwall, M.; Sud, P.: Mendeley readership counts : an investigation of temporal and disciplinary differences (2016) 0.00
    4.1649418E-4 = product of:
      0.009579366 = sum of:
        0.009579366 = product of:
          0.019158732 = sum of:
            0.019158732 = weight(_text_:22 in 3211) [ClassicSimilarity], result of:
              0.019158732 = score(doc=3211,freq=2.0), product of:
                0.08253069 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.023567878 = 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)
      0.04347826 = coord(1/23)
    
    Date
    16.11.2016 11:07:22
  19. Didegah, F.; Thelwall, M.: Co-saved, co-tweeted, and co-cited networks (2018) 0.00
    4.1649418E-4 = product of:
      0.009579366 = sum of:
        0.009579366 = product of:
          0.019158732 = sum of:
            0.019158732 = weight(_text_:22 in 4291) [ClassicSimilarity], result of:
              0.019158732 = score(doc=4291,freq=2.0), product of:
                0.08253069 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.023567878 = 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)
      0.04347826 = coord(1/23)
    
    Date
    28. 7.2018 10:00:22
  20. Thelwall, M.; Prabowo, R.; Fairclough, R.: Are raw RSS feeds suitable for broad issue scanning? : a science concern case study (2006) 0.00
    3.5022903E-4 = product of:
      0.008055268 = sum of:
        0.008055268 = product of:
          0.016110536 = sum of:
            0.016110536 = weight(_text_:29 in 6116) [ClassicSimilarity], result of:
              0.016110536 = score(doc=6116,freq=2.0), product of:
                0.08290443 = queryWeight, product of:
                  3.5176873 = idf(docFreq=3565, maxDocs=44218)
                  0.023567878 = 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)
          0.5 = coord(1/2)
      0.04347826 = coord(1/23)
    
    Date
    21.10.2006 19:29:49