Search (61 results, page 1 of 4)

0.02766634 = product of:
  0.05533268 = sum of:
    0.05533268 = sum of:
      0.0054123 = weight(_text_:a in 77) [ClassicSimilarity], result of:
        0.0054123 = score(doc=77,freq=2.0), product of:
          0.053105544 = queryWeight, product of:
            1.153047 = idf(docFreq=37942, maxDocs=44218)
            0.046056706 = queryNorm
          0.10191591 = fieldWeight in 77, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            1.153047 = idf(docFreq=37942, maxDocs=44218)
            0.0625 = fieldNorm(doc=77)
      0.04992038 = weight(_text_:22 in 77) [ClassicSimilarity], result of:
        0.04992038 = score(doc=77,freq=2.0), product of:
          0.16128273 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.046056706 = 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)

Date

4.12.2006 12:12:22

Type

a

0.025444586 = product of:
  0.05088917 = sum of:
    0.05088917 = sum of:
      0.006765375 = weight(_text_:a in 2808) [ClassicSimilarity], result of:
        0.006765375 = score(doc=2808,freq=8.0), product of:
          0.053105544 = queryWeight, product of:
            1.153047 = idf(docFreq=37942, maxDocs=44218)
            0.046056706 = queryNorm
          0.12739488 = fieldWeight in 2808, product of:
            2.828427 = tf(freq=8.0), with freq of:
              8.0 = termFreq=8.0
            1.153047 = idf(docFreq=37942, maxDocs=44218)
            0.0390625 = fieldNorm(doc=2808)
      0.0441238 = weight(_text_:22 in 2808) [ClassicSimilarity], result of:
        0.0441238 = score(doc=2808,freq=4.0), product of:
          0.16128273 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.046056706 = queryNorm
          0.27358043 = fieldWeight in 2808, 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=2808)
  0.5 = coord(1/2)

Abstract

Internet based electronic resources are growing dramatically but there have been no empirical studies evaluating the impact of e-sources, as a whole, on formal scholarly communication. reports results of an investigation into how much e-sources have been used in formal scholarly communication, using a case study in the area of Library and Information Science (LIS) during the period 1994 to 1996. 4 citation based indicators were used in the study of the impact measurement. Concludes that, compared with the impact of print sources, the impact of e-sources on formal scholarly communication in LIS is small, as measured by e-sources cited, and does not increase significantly by year even though there is observable growth of these impact across the years. It is found that periodical format is related to the rate of citing e-sources, articles are more likely to cite e-sources than are print priodical articles. However, once authors cite electronic resource, there is no significant difference in the number of references per article by periodical format or by year. Suggests that, at this stage, citing e-sources may depend on authors rather than the periodical format in which authors choose to publish

Date

30. 1.1999 17:22:22

Type

a

0.025188856 = product of:
  0.05037771 = sum of:
    0.05037771 = sum of:
      0.00669738 = weight(_text_:a in 108) [ClassicSimilarity], result of:
        0.00669738 = score(doc=108,freq=4.0), product of:
          0.053105544 = queryWeight, product of:
            1.153047 = idf(docFreq=37942, maxDocs=44218)
            0.046056706 = queryNorm
          0.12611452 = fieldWeight in 108, product of:
            2.0 = tf(freq=4.0), with freq of:
              4.0 = termFreq=4.0
            1.153047 = idf(docFreq=37942, maxDocs=44218)
            0.0546875 = fieldNorm(doc=108)
      0.043680333 = weight(_text_:22 in 108) [ClassicSimilarity], result of:
        0.043680333 = score(doc=108,freq=2.0), product of:
          0.16128273 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.046056706 = queryNorm
          0.2708308 = fieldWeight in 108, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.0546875 = fieldNorm(doc=108)
  0.5 = coord(1/2)

Abstract

Citation analysis has long been used by librarians as an important tool of collection development and the advent of Internet technology and especially the WWW adds a new facet to the role played by citation analysis. One of the reasons why librarians create WWW homepages is to provide users with further sources of interest or reference and to do this libraries include links from their own homepages to other information sources. Reports current research on the analysis of WWW pages as an introduction to an examination of the homepages of 25 art libraries to determine what sites are most often included. The types of linked sites are analyzed based on 3 criteria: location, focus and evidence that the link was evaluated before the connection was establisheds

Date

10. 1.1999 16:22:37

Type

a

0.023258494 = product of:
  0.04651699 = sum of:
    0.04651699 = sum of:
      0.009076704 = weight(_text_:a in 2742) [ClassicSimilarity], result of:
        0.009076704 = score(doc=2742,freq=10.0), product of:
          0.053105544 = queryWeight, product of:
            1.153047 = idf(docFreq=37942, maxDocs=44218)
            0.046056706 = queryNorm
          0.1709182 = fieldWeight in 2742, product of:
            3.1622777 = tf(freq=10.0), with freq of:
              10.0 = termFreq=10.0
            1.153047 = idf(docFreq=37942, maxDocs=44218)
            0.046875 = fieldNorm(doc=2742)
      0.037440285 = weight(_text_:22 in 2742) [ClassicSimilarity], result of:
        0.037440285 = score(doc=2742,freq=2.0), product of:
          0.16128273 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.046056706 = queryNorm
          0.23214069 = fieldWeight in 2742, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.046875 = fieldNorm(doc=2742)
  0.5 = coord(1/2)

Abstract

In this research, we aim to identify factors that significantly affect the clickthrough of Web searchers. Our underlying goal is determine more efficient methods to optimize the clickthrough rate. We devise a clickthrough metric for measuring customer satisfaction of search engine results using the number of links visited, number of queries a user submits, and rank of clicked links. We use a neural network to detect the significant influence of searching characteristics on future user clickthrough. Our results show that high occurrences of query reformulation, lengthy searching duration, longer query length, and the higher ranking of prior clicked links correlate positively with future clickthrough. We provide recommendations for leveraging these findings for improving the performance of search engine retrieval and result ranking, along with implications for search engine marketing.

Date

22. 3.2009 17:49:11

Type

a

0.022779368 = product of:
  0.045558736 = sum of:
    0.045558736 = sum of:
      0.008118451 = weight(_text_:a in 6389) [ClassicSimilarity], result of:
        0.008118451 = score(doc=6389,freq=8.0), product of:
          0.053105544 = queryWeight, product of:
            1.153047 = idf(docFreq=37942, maxDocs=44218)
            0.046056706 = queryNorm
          0.15287387 = fieldWeight in 6389, product of:
            2.828427 = tf(freq=8.0), with freq of:
              8.0 = termFreq=8.0
            1.153047 = idf(docFreq=37942, maxDocs=44218)
            0.046875 = fieldNorm(doc=6389)
      0.037440285 = weight(_text_:22 in 6389) [ClassicSimilarity], result of:
        0.037440285 = score(doc=6389,freq=2.0), product of:
          0.16128273 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.046056706 = queryNorm
          0.23214069 = fieldWeight in 6389, 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=6389)
  0.5 = coord(1/2)

Abstract

Examines the use of networked information sources in scholarly communication. Networked information sources are defined broadly to cover: documents and images stored on electronic network hosts; data files; newsgroups; listservs; online information services and electronic periodicals. Reports results of a survey to determine how heavily, if at all, networked information sources are cited in scholarly printed periodicals published in 1993 and 1994. 27 printed periodicals, representing a wide range of subjects and the most influential periodicals in their fields, were identified through the Science Citation Index and Social Science Citation Index Journal Citation Reports. 97 articles were selected for further review and references, footnotes and bibliographies were checked for references to networked information sources. Only 2 articles were found to contain such references. Concludes that, although networked information sources facilitate scholars' work to a great extent during the research process, scholars have yet to incorporate such sources in the bibliographies of their published articles

Source

IFLA journal. 22(1996) no.3, S.240-245

Type

a

0.00334869 = product of:
  0.00669738 = sum of:
    0.00669738 = product of:
      0.01339476 = sum of:
        0.01339476 = weight(_text_:a in 1066) [ClassicSimilarity], result of:
          0.01339476 = score(doc=1066,freq=16.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.25222903 = fieldWeight in 1066, product of:
              4.0 = tf(freq=16.0), with freq of:
                16.0 = termFreq=16.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0546875 = fieldNorm(doc=1066)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Previous studies of academic web interlinking have tended to hypothesise that the relationship between the research of a university and links to or from its web site should follow a linear trend, yet the typical distribution of web data, in general, seems to be a non-linear power law. This paper assesses whether a linear trend or a power law is the most appropriate method with which to model the relationship between research and web site size or outlinks. Following linear regression, analysis of the confidence intervals for the logarithmic graphs, and analysis of the outliers, the results suggest that a linear trend is more appropriate than a non-linear power law.

Type

a

0.0029000505 = product of:
  0.005800101 = sum of:
    0.005800101 = product of:
      0.011600202 = sum of:
        0.011600202 = weight(_text_:a in 3088) [ClassicSimilarity], result of:
          0.011600202 = score(doc=3088,freq=12.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.21843673 = fieldWeight in 3088, product of:
              3.4641016 = tf(freq=12.0), with freq of:
                12.0 = termFreq=12.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0546875 = fieldNorm(doc=3088)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

In this article, we define webometrics within the framework of informetric studies and bibliometrics, as belonging to library and information science, and as associated with cybermetrics as a generic subfield. We develop a consistent and detailed link typology and terminology and make explicit the distinction among different Web node levels when using the proposed conceptual framework. As a consequence, we propose a novel diagram notation to fully appreciate and investigate link structures between Web nodes in webometric analyses. We warn against taking the analogy between citation analyses and link analyses too far.

Type

a

0.0028703054 = product of:
  0.005740611 = sum of:
    0.005740611 = product of:
      0.011481222 = sum of:
        0.011481222 = weight(_text_:a in 2571) [ClassicSimilarity], result of:
          0.011481222 = score(doc=2571,freq=16.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.2161963 = fieldWeight in 2571, product of:
              4.0 = tf(freq=16.0), with freq of:
                16.0 = termFreq=16.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046875 = fieldNorm(doc=2571)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

A common task in both Webmetrics and Web information retrieval is to identify a set of Web pages or sites that are similar in content. In this paper we assess the extent to which links, colinks and couplings can be used to identify similar Web sites. As an experiment, a random sample of 500 pairs of domains from the UK academic Web were taken and human assessments of site similarity, based upon content type, were compared against ratings for the three concepts. The results show that using a combination of all three gives the highest probability of identifying similar sites, but surprisingly this was only a marginal improvement over using links alone. Another unexpected result was that high values for either colink counts or couplings were associated with only a small increased likelihood of similarity. The principal advantage of using couplings and colinks was found to be greater coverage in terms of a much larger number of pairs of sites being connected by these measures, instead of increased probability of similarity. In information retrieval terminology, this is improved recall rather than improved precision.

Type

a

0.0026473717 = product of:
  0.0052947435 = sum of:
    0.0052947435 = product of:
      0.010589487 = sum of:
        0.010589487 = weight(_text_:a in 2886) [ClassicSimilarity], result of:
          0.010589487 = score(doc=2886,freq=10.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.19940455 = fieldWeight in 2886, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0546875 = fieldNorm(doc=2886)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

The present paper analyzes the changes that occurred to a set of Web pages related to "informetrics" over a period of 5 years between June 1998 and June 2003. Four times during this time span, in 1998,1999, 2002, and 2003, we monitored previously located pages and searched for new ones related to the topic. Thus, we were able to study the growth of the topic, white analyzing the rates of change and disappearance. The results indicate that modification, disappearance, and resurfacing cannot be ignored when studying the structure and development of the Web.

Type

a

0.0024857575 = product of:
  0.004971515 = sum of:
    0.004971515 = product of:
      0.00994303 = sum of:
        0.00994303 = weight(_text_:a in 3095) [ClassicSimilarity], result of:
          0.00994303 = score(doc=3095,freq=12.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.18723148 = fieldWeight in 3095, product of:
              3.4641016 = tf(freq=12.0), with freq of:
                12.0 = termFreq=12.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046875 = fieldNorm(doc=3095)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

The Web is a huge source of information, and one of the main problems facing users is finding documents which correspond to their requirements. Apart from the problem of thematic relevance, the documents retrieved by search engines do not always meet the users' expectations. The document may be too general, or conversely too specialized, or of a different type from what the user is looking for, and so forth. We think that adding metadata to pages can considerably improve the process of searching for information an the Web. This article presents a possible typology for Web sites and pages, as weIl as a method for propagating metadata values, based an the study of the Web graph and more specifically the method of cocitation in this graph.

Type

a

0.0024857575 = product of:
  0.004971515 = sum of:
    0.004971515 = product of:
      0.00994303 = sum of:
        0.00994303 = weight(_text_:a in 4908) [ClassicSimilarity], result of:
          0.00994303 = score(doc=4908,freq=12.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.18723148 = fieldWeight in 4908, product of:
              3.4641016 = tf(freq=12.0), with freq of:
                12.0 = termFreq=12.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046875 = fieldNorm(doc=4908)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Link analysis in various forms is now an established technique in many different subjects, reflecting the perceived importance of links and of the Web. A critical but very difficult issue is how to interpret the results of social science link analyses. lt is argued that the dynamic nature of the Web, its lack of quality control, and the online proliferation of copying and imitation mean that methodologies operating within a highly positivist, quantitative framework are ineffective. Conversely, the sheer variety of the Web makes application of qualitative methodologies and pure reason very problematic to large-scale studies. Methodology triangulation is consequently advocated, in combination with a warning that the Web is incapable of giving definitive answers to large-scale link analysis research questions concerning social factors underlying link creation. Finally, it is claimed that although theoretical frameworks are appropriate for guiding research, a Theory of Link Analysis is not possible.

Type

a

0.0024857575 = product of:
  0.004971515 = sum of:
    0.004971515 = product of:
      0.00994303 = sum of:
        0.00994303 = weight(_text_:a in 153) [ClassicSimilarity], result of:
          0.00994303 = score(doc=153,freq=12.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.18723148 = fieldWeight in 153, product of:
              3.4641016 = tf(freq=12.0), with freq of:
                12.0 = termFreq=12.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046875 = fieldNorm(doc=153)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Information grounds emerge as people share information with others in a common place. Many studies have investigated the emergence of information grounds in public places. This study pays attention to the emergence, peak, and abeyance of an online information ground. It investigates a Facebook group used by youth for sharing information when misinformation spread wildly during the 2011 violence in Ambon, Indonesia. The findings demonstrate change and continuity in an online information ground; it became an information hub when reaching a peak cycle, and an information repository when entering into abeyance. Despite this period of nonactivity, the friendships and collective memories resulting from information ground interactions last over time and can be used for reactivating the online information ground when new needs emerge. Illuminating the lifecycles of an online information ground, the findings have potential to explain the dynamic of users' interactions with others and with information in quotidian spaces.

Type

a

0.0023678814 = product of:
  0.0047357627 = sum of:
    0.0047357627 = product of:
      0.009471525 = sum of:
        0.009471525 = weight(_text_:a in 1071) [ClassicSimilarity], result of:
          0.009471525 = score(doc=1071,freq=8.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.17835285 = fieldWeight in 1071, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0546875 = fieldNorm(doc=1071)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Reports investigations into the feasibility and reliability of calculating impact factors for web sites, called Web Impact Factors (Web-IF). analyzes a selection of 7 small and medium scale national and 4 large web domains as well as 6 institutional web sites over a series of snapshots taken of the web during a month. Describes the data isolation and calculation methods and discusses the tests. The results thus far demonstrate that Web-IFs are calculable with high confidence for national and sector domains whilst institutional Web-IFs should be approached with caution

Type

a

0.0023678814 = product of:
  0.0047357627 = sum of:
    0.0047357627 = product of:
      0.009471525 = sum of:
        0.009471525 = weight(_text_:a in 1252) [ClassicSimilarity], result of:
          0.009471525 = score(doc=1252,freq=8.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.17835285 = fieldWeight in 1252, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0546875 = fieldNorm(doc=1252)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

The data systems, policies and procedures, corporate culture, and public face of an agency or institution make up its organizational interface. This case study describes how user interfaces for the Bureau of Labor Statistics web site evolved over a 5-year period along with the [arger organizational interface and how this co-evolution has influenced the institution itself. Interviews with BLS staff and transaction log analysis are the foci in this analysis that also included user informationseeking studies and user interface prototyping and testing. The results are organized into a model of organizational interface change and related to the information life cycle.

Type

a

0.0023678814 = product of:
  0.0047357627 = sum of:
    0.0047357627 = product of:
      0.009471525 = sum of:
        0.009471525 = weight(_text_:a in 3089) [ClassicSimilarity], result of:
          0.009471525 = score(doc=3089,freq=8.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.17835285 = fieldWeight in 3089, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0546875 = fieldNorm(doc=3089)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

In this article, I investigate the reliability, in the social science sense, of collecting informetric data about the World Wide Web by Web crawling. The investigation includes a critical examination of the practice of Web crawling and contrasts the results of content crawling with the results of link crawling. It is shown that Web crawling by search engines is intentionally biased and selective. I also report the results of a [arge-scale experimental simulation of Web crawling that illustrates the effects of different crawling policies an data collection. It is concluded that the reliability of Web crawling as a data collection technique is improved by fuller reporting of relevant crawling policies.

Type

a

0.0023678814 = product of:
  0.0047357627 = sum of:
    0.0047357627 = product of:
      0.009471525 = sum of:
        0.009471525 = weight(_text_:a in 3890) [ClassicSimilarity], result of:
          0.009471525 = score(doc=3890,freq=2.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.17835285 = fieldWeight in 3890, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.109375 = fieldNorm(doc=3890)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Type

a

0.0023435948 = product of:
  0.0046871896 = sum of:
    0.0046871896 = product of:
      0.009374379 = sum of:
        0.009374379 = weight(_text_:a in 2908) [ClassicSimilarity], result of:
          0.009374379 = score(doc=2908,freq=6.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.17652355 = fieldWeight in 2908, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0625 = fieldNorm(doc=2908)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Webometrics, the quantitative study of Web phenomena, is a field encompassing contributions from information science, computer science, and statistical physics. Its methodology draws especially from bibliometrics. This special issue presents contributions that both push for ward the field and illustrate a wide range of webometric approaches.

Type

a

0.002269176 = product of:
  0.004538352 = sum of:
    0.004538352 = product of:
      0.009076704 = sum of:
        0.009076704 = weight(_text_:a in 4474) [ClassicSimilarity], result of:
          0.009076704 = score(doc=4474,freq=10.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.1709182 = fieldWeight in 4474, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046875 = fieldNorm(doc=4474)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

There has been much recent interest in extracting information from collections of Web links. One tool that has been used is Ingwersen's Web impact factor. It has been demonstrated that several versions of this metric can produce results that correlate with research ratings of British universities showing that, despite being a measure of a purely Internet phenomenon, the results are susceptible to a wider interpretation. This paper addresses the question of which is the best possible domain to count backlinks from, if research is the focus of interest. WIFs for British universities calculated from several different source domains are compared, primarily the .edu, .ac.uk and .uk domains, and the entire Web. The results show that all four areas produce WIFs that correlate strongly with research ratings, but that none produce incontestably superior figures. It was also found that the WIF was less able to differentiate in more homogeneous subsets of universities, although positive results are still possible.

Type

a

0.002269176 = product of:
  0.004538352 = sum of:
    0.004538352 = product of:
      0.009076704 = sum of:
        0.009076704 = weight(_text_:a in 3782) [ClassicSimilarity], result of:
          0.009076704 = score(doc=3782,freq=10.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.1709182 = fieldWeight in 3782, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046875 = fieldNorm(doc=3782)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

With the rise of Wikipedia as a first-stop source for scientific information, it is important to understand whether Wikipedia draws upon the research that scientists value most. Here we identify the 250 most heavily used journals in each of 26 research fields (4,721 journals, 19.4M articles) indexed by the Scopus database, and test whether topic, academic status, and accessibility make articles from these journals more or less likely to be referenced on Wikipedia. We find that a journal's academic status (impact factor) and accessibility (open access policy) both strongly increase the probability of it being referenced on Wikipedia. Controlling for field and impact factor, the odds that an open access journal is referenced on the English Wikipedia are 47% higher compared to paywall journals. These findings provide evidence is that a major consequence of open access policies is to significantly amplify the diffusion of science, through an intermediary like Wikipedia, to a broad audience.

Type

a

0.0022374375 = product of:
  0.004474875 = sum of:
    0.004474875 = product of:
      0.00894975 = sum of:
        0.00894975 = weight(_text_:a in 4533) [ClassicSimilarity], result of:
          0.00894975 = score(doc=4533,freq=14.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.1685276 = fieldWeight in 4533, product of:
              3.7416575 = tf(freq=14.0), with freq of:
                14.0 = termFreq=14.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4533)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Purpose - Link analysis is an established topic within webometrics. It normally uses counts of links between sets of web sites or to sets of web sites. These link counts are derived from web crawlers or commercial search engines with the latter being the only alternative for some investigations. This paper compares link counts with URL citation counts in order to assess whether the latter could be a replacement for the former if the major search engines withdraw their advanced hyperlink search facilities. Design/methodology/approach - URL citation counts are compared with link counts for a variety of data sets used in previous webometric studies. Findings - The results show a high degree of correlation between the two but with URL citations being much less numerous, at least outside academia and business. Research limitations/implications - The results cover a small selection of 15 case studies and so the findings are only indicative. Significant differences between results indicate that the difference between link counts and URL citation counts will vary between webometric studies. Practical implications - Should link searches be withdrawn, then link analyses of less well linked non-academic, non-commercial sites would be seriously weakened, although citations based on e-mail addresses could help to make citations more numerous than links for some business and academic contexts. Originality/value - This is the first systematic study of the difference between link counts and URL citation counts in a variety of contexts and it shows that there are significant differences between the two.

Type

a