Search (26 results, page 1 of 2)

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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

Source

Journal of the American Society for Information Science and Technology. 60(2009) no.3, S.434-442

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Abstract

The quality and impact of academic Web sites is of interest to many audiences, including the scholars who use them and Web educators who need to identify best practice. Several large-scale European Union research projects have been funded to build new indicators for online scientific activity, reflecting recognition of the importance of the Web for scholarly communication. In this paper we address the key question of whether higher rated scholars produce higher impact Web sites, using the United Kingdom as a case study and measuring scholars' quality in terms of university-wide average research ratings. Methodological issues concerning the measurement of the online impact are discussed, leading to the adoption of counts of links to a university's constituent single domain Web sites from an aggregated counting metric. The findings suggest that universities with higher rated scholars produce significantly more Web content but with a similar average online impact. Higher rated scholars therefore attract more total links from their peers, but only by being more prolific, refuting earlier suggestions. It can be surmised that general Web publications are very different from scholarly journal articles and conference papers, for which scholarly quality does associate with citation impact. This has important implications for the construction of new Web indicators, for example that online impact should not be used to assess the quality of small groups of scholars, even within a single discipline.

Source

Journal of the American Society for Information Science and technology. 55(2004) no.2, S.149-159

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Abstract

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

Source

Annual review of information science and technology. 39(2005), S.81-138

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Abstract

Much has been written about the potential and pitfalls of macroscopic Web-based link analysis, yet there have been no studies that have provided clear statistical evidence that any of the proposed calculations can produce results over large areas of the Web that correlate with phenomena external to the Internet. This article attempts to provide such evidence through an evaluation of Ingwersen's (1998) proposed external Web Impact Factor (WIF) for the original use of the Web: the interlinking of academic research. In particular, it studies the case of the relationship between academic hyperlinks and research activity for universities in Britain, a country chosen for its variety of institutions and the existence of an official government rating exercise for research. After reviewing the numerous reasons why link counts may be unreliable, it demonstrates that four different WIFs do, in fact, correlate with the conventional academic research measures. The WIF delivering the greatest correlation with research rankings was the ratio of Web pages with links pointing at research-based pages to faculty numbers. The scarcity of links to electronic academic papers in the data set suggests that, in contrast to citation analysis, this WIF is measuring the reputations of universities and their scholars, rather than the quality of their publications

Source

Journal of the American Society for Information Science and technology. 52(2001) no.13, S.1157-1168

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Abstract

Although the analysis of citations in the scholarly literature is now an established and relatively well understood part of information science, not enough is known about citations that can be found on the Web. In particular, are there new Web types, and if so, are these trivial or potentially useful for studying or evaluating research communication? We sought evidence based upon a sample of 1,577 Web citations of the URLs or titles of research articles in 64 open-access journals from biology, physics, chemistry, and computing. Only 25% represented intellectual impact, from references of Web documents (23%) and other informal scholarly sources (2%). Many of the Web/URL citations were created for general or subject-specific navigation (45%) or for self-publicity (22%). Additional analyses revealed significant disciplinary differences in the types of Google unique Web/URL citations as well as some characteristics of scientific open-access publishing on the Web. We conclude that the Web provides access to a new and different type of citation information, one that may therefore enable us to measure different aspects of research, and the research process in particular; but to obtain good information, the different types should be separated.

Source

Journal of the American Society for Information Science and Technology. 58(2007) no.11, S.1631-1644

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Abstract

Webometrics is an information science field concerned with measuring aspects of the World Wide Web (WWW) for a variety of information science research goals. It came into existence about five years after the Web was formed and has since grown to become a significant aspect of information science, at least in terms of published research. Although some webometrics research has focused on the structure or evolution of the Web itself or the performance of commercial search engines, most has used data from the Web to shed light on information provision or online communication in various contexts. Most prominently, techniques have been developed to track, map, and assess Web-based informal scholarly communication, for example, in terms of the hyperlinks between academic Web sites or the online impact of digital repositories. In addition, a range of nonacademic issues and groups of Web users have also been analyzed.

Source

Encyclopedia of library and information sciences. 3rd ed. Ed.: M.J. Bates

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Abstract

Web impact factors, the proposed web equivalent of impact factors for journals, can be calculated by using search engines. It has been found that the results are problematic because of the variable coverage of search engines as well as their ability to give significantly different results over short periods of time. The fundamental problem is that although some search engines provide a functionality that is capable of being used for impact calculations, this is not their primary task and therefore they do not give guarantees as to performance in this respect. In this paper, a bespoke web crawler designed specifically for the calculation of reliable WIFs is presented. This crawler was used to calculate WIFs for a number of UK universities, and the results of these calculations are discussed. The principal findings were that with certain restrictions, WIFs can be calculated reliably, but do not correlate with accepted research rankings owing to the variety of material hosted on university servers. Changes to the calculations to improve the fit of the results to research rankings are proposed, but there are still inherent problems undermining the reliability of the calculation. These problems still apply if the WIF scores are taken on their own as indicators of the general impact of any area of the Internet, but with care would not apply to online journals.

Source

Journal of documentation. 57(2001) no.2, S.177-191

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Abstract

A layered approach for identifying communities in the Web is presented and explored by applying the flake exact community identification algorithm to the UK academic Web. Although community or topic identification is a common task in information retrieval, a new perspective is developed by: the application of alternative document models, shifting the focus from individual pages to aggregated collections based upon Web directories, domains and entire sites; the removal of internal site links; and the adaptation of a new fast algorithm to allow fully-automated community identification using all possible single starting points. The overall topology of the graphs in the three least-aggregated layers was first investigated and found to include a large number of isolated points but, surprisingly, with most of the remainder being in one huge connected component, exact proportions varying by layer. The community identification process then found that the number of communities far exceeded the number of topological components, indicating that community identification is a potentially useful technique, even with random starting points. Both the number and size of communities identified was dependent on the parameter of the algorithm, with very different results being obtained in each case. In conclusion, the UK academic Web is embedded with layers of non-trivial communities and, if it is not unique in this, then there is the promise of improved results for information retrieval algorithms that can exploit this additional structure, and the application of the technique directly to partially automate Web metrics tasks such as that of finding all pages related to a given subject hosted by a single country's universities.

Source

Journal of documentation. 59(2003) no.4, S.410-429

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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.

Footnote

Beitrag in einem "Special Issue on Infometrics"

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Abstract

All known previous Web link studies have used the Web page as the primary indivisible source document for counting purposes. Arguments are presented to explain why this is not necessarily optimal and why other alternatives have the potential to produce better results. This is despite the fact that individual Web files are often the only choice if search engines are used for raw data and are the easiest basic Web unit to identify. The central issue is of defining the Web "document": that which should comprise the single indissoluble unit of coherent material. Three alternative heuristics are defined for the educational arena based upon the directory, the domain and the whole university site. These are then compared by implementing them an a set of 108 UK university institutional Web sites under the assumption that a more effective heuristic will tend to produce results that correlate more highly with institutional research productivity. It was discovered that the domain and directory models were able to successfully reduce the impact of anomalous linking behavior between pairs of Web sites, with the latter being the method of choice. Reasons are then given as to why a document model an its own cannot eliminate all anomalies in Web linking behavior. Finally, the results from all models give a clear confirmation of the very strong association between the research productivity of a UK university and the number of incoming links from its peers' Web sites.

Source

Journal of the American Society for Information Science and technology. 53(2002) no.12, S.995-1005

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Abstract

Open-access online publication has made available an increasingly wide range of document types for scientometric analysis. In this article, we focus on citations in online presentations, seeking evidence of their value as nontraditional indicators of research impact. For this purpose, we searched for online PowerPoint files mentioning any one of 1,807 ISI-indexed journals in ten science and ten social science disciplines. We also manually classified 1,378 online PowerPoint citations to journals in eight additional science and social science disciplines. The results showed that very few journals were cited frequently enough in online PowerPoint files to make impact assessment worthwhile, with the main exceptions being popular magazines like Scientific American and Harvard Business Review. Surprisingly, however, there was little difference overall in the number of PowerPoint citations to science and to the social sciences, and also in the proportion representing traditional impact (about 60%) and wider impact (about 15%). It seems that the main scientometric value for online presentations may be in tracking the popularization of research, or for comparing the impact of whole journals rather than individual articles.

Source

Journal of the American Society for Information Science and Technology. 59(2008) no.5, S.805-815

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Abstract

Interdisciplinary collaboration is a major goal in research policy. This study uses citation analysis to examine diverse subjects in the Web of Science and Scopus to ascertain whether, in general, research published in journals classified in more than one subject is more highly cited than research published in journals classified in a single subject. For each subject, the study divides the journals into two disjoint sets called Multi and Mono. Multi consists of all journals in the subject and at least one other subject whereas Mono consists of all journals in the subject and in no other subject. The main findings are: (a) For social science subject categories in both the Web of Science and Scopus, the average citation levels of articles in Mono and Multi are very similar; and (b) for Scopus subject categories within life sciences, health sciences, and physical sciences, the average citation level of Mono articles is roughly twice that of Multi articles. Hence, one cannot assume that in general, multidisciplinary research will be more highly cited, and the converse is probably true for many areas of science. A policy implication is that, at least in the sciences, multidisciplinary researchers should not be evaluated by citations on the same basis as monodisciplinary researchers.

Object

Web of Science

Source

Journal of the American Society for Information Science and Technology. 59(2008) no.12, S.1973-1984

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Abstract

In recent years, a considerable body of Webometric research has used hyperlinks to generate indicators for the impact of Web documents and the organizations that created them. The relationship between this Web impact and other, offline impact indicators has been explored for entire universities, departments, countries, and scientific journals, but not yet for individual scientists-an important omission. The present research closes this gap by investigating factors that may influence the Web impact (i.e., inlink counts) of scientists' personal homepages. Data concerning 456 scientists from five scientific disciplines in six European countries were analyzed, showing that both homepage content and personal and institutional characteristics of the homepage owners had significant relationships with inlink counts. A multivariate statistical analysis confirmed that full-text articles are the most linked-to content in homepages. At the individual homepage level, hyperlinks are related to several offline characteristics. Notable differences regarding total inlinks to scientists' homepages exist between the scientific disciplines and the countries in the sample. There also are both gender and age effects: fewer external inlinks (i.e., links from other Web domains) to the homepages of female and of older scientists. There is only a weak relationship between a scientist's recognition and homepage inlinks and, surprisingly, no relationship between research productivity and inlink counts. Contrary to expectations, the size of collaboration networks is negatively related to hyperlink counts. Some of the relationships between hyperlinks to homepages and the properties of their owners can be explained by the content that the homepage owners put on their homepage and their level of Internet use; however, the findings about productivity and collaborations do not seem to have a simple, intuitive explanation. Overall, the results emphasize the complexity of the phenomenon of Web linking, when analyzed at the level of individual pages.

Source

Journal of the American Society for Information Science and Technology. 58(2007) no.2, S.200-211

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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.

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Date

4.12.2006 12:12:22

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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.

Source

Journal of the American Society for Information Science and Technology. 57(2006) no.1, S.60-68

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Abstract

Bibliometrics has changed out of all recognition since 1958; becoming established as a field, being taught widely in library and information science schools, and being at the core of a number of science evaluation research groups around the world. This was all made possible by the work of Eugene Garfield and his Science Citation Index. This article reviews the distance that bibliometrics has travelled since 1958 by comparing early bibliometrics with current practice, and by giving an overview of a range of recent developments, such as patent analysis, national research evaluation exercises, visualization techniques, new applications, online citation indexes, and the creation of digital libraries. Webometrics, a modern, fast-growing offshoot of bibliometrics, is reviewed in detail. Finally, future prospects are discussed with regard to both bibliometrics and webometrics.

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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.

Source

Journal of documentation. 58(2002) no.1, S.66-78

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Abstract

Search engines are normally used to find information or Web sites, but Webometric investigations use them for quantitative data such as the number of pages matching a query and the international spread of those pages. For this type of application, the accuracy of the hit count estimates and range of URLs in the full results are important. Here, we compare the applications programming interfaces of Google, Yahoo!, and Live Search for 1,587 single word searches. The hit count estimates were broadly consistent but with Yahoo! and Google, reporting 5-6 times more hits than Live Search. Yahoo! tended to return slightly more matching URLs than Google, with Live Search returning significantly fewer. Yahoo!'s result URLs included a significantly wider range of domains and sites than the other two, and there was little consistency between the three engines in the number of different domains. In contrast, the three engines were reasonably consistent in the number of different top-level domains represented in the result URLs, although Yahoo! tended to return the most. In conclusion, quantitative results from the three search engines are mostly consistent but with unexpected types of inconsistency that users should be aware of. Google is recommended for hit count estimates but Yahoo! is recommended for all other Webometric purposes.

Source

Journal of the American Society for Information Science and Technology. 59(2008) no.11, S.1702-1710

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Source

Journal of information science. 30(2005) no.5, S.436-