Search (7 results, page 1 of 1)

7.9397525E-4 = product of:
  0.0055578267 = sum of:
    0.0055578267 = product of:
      0.027789133 = sum of:
        0.027789133 = weight(_text_:system in 1065) [ClassicSimilarity], result of:
          0.027789133 = score(doc=1065,freq=2.0), product of:
            0.11408355 = queryWeight, product of:
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.03622214 = queryNorm
            0.2435858 = fieldWeight in 1065, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.0546875 = fieldNorm(doc=1065)
      0.2 = coord(1/5)
  0.14285715 = coord(1/7)

Abstract

This article reveals different patterns of scholarly communication in the XML research field on the Web and in print journals in terms of author visibility, and challenges the common practice of exclusively using the ISI's databases to obtain citation counts as scientific performance indicators. Results from this study demonstrate both the importance and the feasibility of the use of multiple citation data sources in citation analysis studies of scholarly communication, and provide evidence for a developing "two tier" scholarly communication system.

6.2775286E-4 = product of:
  0.00439427 = sum of:
    0.00439427 = product of:
      0.02197135 = sum of:
        0.02197135 = weight(_text_:retrieval in 1720) [ClassicSimilarity], result of:
          0.02197135 = score(doc=1720,freq=2.0), product of:
            0.109568894 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.03622214 = queryNorm
            0.20052543 = fieldWeight in 1720, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.046875 = fieldNorm(doc=1720)
      0.2 = coord(1/5)
  0.14285715 = coord(1/7)

Abstract

Using an enriched author cocitation analysis (ACA), we map information science (IS) for 1996-2005, a decade of explosive development of the World Wide Web, to examine its development since the landmark study by White and McCain (1998). The Web, we find, has had a profound impact on IS, driving the creation of new disciplines and revitalization or obsolescence of old, and most importantly, bridging the chasm between the literatures and retrieval IS camps. Simultaneously, the development of IS towards cognitive aspects has intensified. Our study enriches classic ACA in that it employs both orthogonal and oblique rotations in the factor analysis (FA), and reports both pattern and structure matrices for the latter, thus enabling a comparison between these several FA methods in ACA. Each method provides interesting information not available from the others, we find, especially when results are also visualized in the novel manner we introduce here.

5.6712516E-4 = product of:
  0.003969876 = sum of:
    0.003969876 = product of:
      0.01984938 = sum of:
        0.01984938 = weight(_text_:system in 471) [ClassicSimilarity], result of:
          0.01984938 = score(doc=471,freq=2.0), product of:
            0.11408355 = queryWeight, product of:
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.03622214 = queryNorm
            0.17398985 = fieldWeight in 471, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.0390625 = fieldNorm(doc=471)
      0.2 = coord(1/5)
  0.14285715 = coord(1/7)

Abstract

We present evidence that in some research fields, research published in journals and reported on the Web may collectively represent different evolutionary stages of the field, with journals lagging a few years behind the Web on average, and that a "two-tier" scholarly communication system may therefore be evolving. We conclude that in such fields, (a) for detecting current research fronts, author co-citation analyses (ACA) using articles published on the Web as a data source can outperform traditional ACAs using articles published in journals as data, and that (b) as a result, it is important to use multiple data sources in citation analysis studies of scholarly communication for a complete picture of communication patterns. Our evidence stems from comparing the respective intellectual structures of the XML research field, a subfield of computer science, as revealed from three sets of ACA covering two time periods: (a) from the field's beginnings in 1996 to 2001, and (b) from 2001 to 2006. For the first time period, we analyze research articles both from journals as indexed by the Science Citation Index (SCI) and from the Web as indexed by CiteSeer. We follow up by an ACA of SCI data for the second time period. We find that most trends in the evolution of this field from the first to the second time period that we find when comparing ACA results from the SCI between the two time periods already were apparent in the ACA results from CiteSeer during the first time period.

5.2312744E-4 = product of:
  0.003661892 = sum of:
    0.003661892 = product of:
      0.01830946 = sum of:
        0.01830946 = weight(_text_:retrieval in 389) [ClassicSimilarity], result of:
          0.01830946 = score(doc=389,freq=2.0), product of:
            0.109568894 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.03622214 = queryNorm
            0.16710453 = fieldWeight in 389, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.0390625 = fieldNorm(doc=389)
      0.2 = coord(1/5)
  0.14285715 = coord(1/7)

Abstract

In this article, we explore how strongly author name disambiguation (AND) affects the results of an author-based citation analysis study, and identify conditions under which the traditional simplified approach of using surnames and first initials may suffice in practice. We compare author citation ranking and cocitation mapping results in the stem cell research field from 2004 to 2009 using two AND approaches: the traditional simplified approach of using author surname and first initial and a sophisticated algorithmic approach. We find that the traditional approach leads to extremely distorted rankings and substantially distorted mappings of authors in this field when based on first- or all-author citation counting, whereas last-author-based citation ranking and cocitation mapping both appear relatively immune to the author name ambiguity problem. This is largely because Romanized names of Chinese and Korean authors, who are very active in this field, are extremely ambiguous, but few of these researchers consistently publish as last authors in bylines. We conclude that a more earnest effort is required to deal with the author name ambiguity problem in both citation analysis and information retrieval, especially given the current trend toward globalization. In the stem cell research field, in which laboratory heads are traditionally listed as last authors in bylines, last-author-based citation ranking and cocitation mapping using the traditional approach to author name disambiguation may serve as a simple workaround, but likely at the price of largely filtering out Chinese and Korean contributions to the field as well as important contributions by young researchers.

5.2312744E-4 = product of:
  0.003661892 = sum of:
    0.003661892 = product of:
      0.01830946 = sum of:
        0.01830946 = weight(_text_:retrieval in 1259) [ClassicSimilarity], result of:
          0.01830946 = score(doc=1259,freq=2.0), product of:
            0.109568894 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.03622214 = queryNorm
            0.16710453 = fieldWeight in 1259, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.0390625 = fieldNorm(doc=1259)
      0.2 = coord(1/5)
  0.14285715 = coord(1/7)

Abstract

This study continues a long history of author cocitation analysis (and more recently, author bibliographic coupling analysis) of the intellectual structure of information science (IS) into the time period 2006 to 2010 (IS 2006-2010). We find that web technologies continue to drive developments, especially at the research front, although perhaps more indirectly than before. A broadening of perspectives is visible in IS 2006-2010, where network science becomes influential and where full-text analysis methods complement traditional computer science influences. Research in the areas of the h-index and mapping of science appears to have been highlights of IS 2006-2011. This study tests and confirms a forecast made previously by comparing knowledge-base and research-front findings for IS 2001-2005, which expected both the information retrieval (IR) systems and webometrics specialties to shrink in 2006 to 2010. A corresponding comparison of the knowledge base and research front of IS 2006-2010 suggests a continuing decline of the IR systems specialty in the near future, but also a considerable (re)growth of the webometrics area after a period of decline from 2001 to 2005 and 2006 to 2010, with the latter due perhaps in part to its contribution to an emerging web science.

4.1850194E-4 = product of:
  0.0029295133 = sum of:
    0.0029295133 = product of:
      0.014647567 = sum of:
        0.014647567 = weight(_text_:retrieval in 608) [ClassicSimilarity], result of:
          0.014647567 = score(doc=608,freq=2.0), product of:
            0.109568894 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.03622214 = queryNorm
            0.13368362 = fieldWeight in 608, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.03125 = fieldNorm(doc=608)
      0.2 = coord(1/5)
  0.14285715 = coord(1/7)

Abstract

Purpose Wikipedia has the lofty goal of compiling all human knowledge. The purpose of the present study is to map the structure of the Traditional Chinese Medicine (TCM) knowledge domain on Wikipedia, to identify patterns of knowledge representation on Wikipedia and to test the applicability of author bibliographic coupling analysis, an effective method for mapping knowledge domains represented in published scholarly documents, for Wikipedia data. Design/methodology/approach We adapted and followed the well-established procedures and techniques for author bibliographic coupling analysis (ABCA). Instead of bibliographic data from a citation database, we used all articles on TCM downloaded from the English version of Wikipedia as our dataset. An author bibliographic coupling network was calculated and then factor analyzed using SPSS. Factor analysis results were visualized. Factors were labeled upon manual examination of articles that authors who load primarily in each factor have significantly contributed references to. Clear factors were interpreted as topics. Findings Seven TCM topic areas are represented on Wikipedia, among which Acupuncture-related practices, Falun Gong and Herbal Medicine attracted the most significant contributors to TCM. Acupuncture and Qi Gong have the most connections to the TCM knowledge domain and also serve as bridges for other topics to connect to the domain. Herbal medicine is weakly linked to and non-herbal medicine is isolated from the rest of the TCM knowledge domain. It appears that specific topics are represented well on Wikipedia but their conceptual connections are not. ABCA is effective for mapping knowledge domains on Wikipedia but document-based bibliographic coupling analysis is not. Originality/value Given the prominent position of Wikipedia for both information users and for researchers on knowledge organization and information retrieval, it is important to study how well knowledge is represented and structured on Wikipedia. Such studies appear largely missing although studies from different perspectives both about Wikipedia and using Wikipedia as data are abundant. Author bibliographic coupling analysis is effective for mapping knowledge domains represented in published scholarly documents but has never been applied to mapping knowledge domains represented on Wikipedia.

4.1850194E-4 = product of:
  0.0029295133 = sum of:
    0.0029295133 = product of:
      0.014647567 = sum of:
        0.014647567 = weight(_text_:retrieval in 610) [ClassicSimilarity], result of:
          0.014647567 = score(doc=610,freq=2.0), product of:
            0.109568894 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.03622214 = queryNorm
            0.13368362 = fieldWeight in 610, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.03125 = fieldNorm(doc=610)
      0.2 = coord(1/5)
  0.14285715 = coord(1/7)

Abstract

Purpose This study continues a long history of author co-citation analysis of the intellectual structure of information science into the time period of 2011-2020. It also examines changes in this structure from 2006-2010 through 2011-2015 to 2016-2020. Results will contribute to a better understanding of the information science research field. Design/methodology/approach The well-established procedures and techniques for author co-citation analysis were followed. Full records of research articles in core information science journals published during 2011-2020 were retrieved and downloaded from the Web of Science database. About 150 most highly cited authors in each of the two five-year time periods were selected from this dataset to represent this field, and their co-citation counts were calculated. Each co-citation matrix was input into SPSS for factor analysis, and results were visualized in Pajek. Factors were interpreted as specialties and labeled upon an examination of articles written by authors who load primarily on each factor. Findings The two-camp structure of information science continued to be present clearly. Bibliometric indicators for research evaluation dominated the Knowledge Domain Analysis camp during both fivr-year time periods, whereas interactive information retrieval (IR) dominated the IR camp during 2011-2015 but shared dominance with information behavior during 2016-2020. Bridging between the two camps became increasingly weaker and was only provided by the scholarly communication specialty during 2016-2020. The IR systems specialty drifted further away from the IR camp. The information behavior specialty experienced a deep slump during 2011-2020 in its evolution process. Altmetrics grew to dominate the Webometrics specialty and brought it to a sharp increase during 2016-2020. Originality/value Author co-citation analysis (ACA) is effective in revealing intellectual structures of research fields. Most related studies used term-based methods to identify individual research topics but did not examine the interrelationships between these topics or the overall structure of the field. The few studies that did discuss the overall structure paid little attention to the effect of changes to the source journals on the results. The present study does not have these problems and continues the long history of benchmark contributions to a better understanding of the information science field using ACA.