Search (22 results, page 1 of 2)

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Abstract

The primary webometric method for estimating the online impact of an organization is to count links to its website. Link counts have been available from commercial search engines for over a decade but this was set to end by early 2012 and so a replacement is needed. This article compares link counts to two alternative methods: URL citations and organization title mentions. New variations of these methods are also introduced. The three methods are compared against each other using Yahoo!. Two of the three methods (URL citations and organization title mentions) are also compared against each other using Bing. Evidence from a case study of 131 UK universities and 49 US Library and Information Science (LIS) departments suggests that Bing's Hit Count Estimates (HCEs) for popular title searches are not useful for webometric research but that Yahoo!'s HCEs for all three types of search and Bing's URL citation HCEs seem to be consistent. For exact URL counts the results of all three methods in Yahoo! and both methods in Bing are also consistent. Four types of accuracy factors are also introduced and defined: search engine coverage, search engine retrieval variation, search engine retrieval anomalies, and query polysemy.

Source

Journal of the American Society for Information Science and Technology. 62(2011) no.8, S.1488-1497

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Date

4.12.2006 12:12:22

Source

Information - Wissenschaft und Praxis. 57(2006) H.8, S.401-406

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Date

22. 1.2011 14:27:06

Source

Journal of the American Society for Information Science and Technology. 62(2011) no.2, S.406-418

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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

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.

Source

Journal of the American Society for Information Science and Technology. 55(2004) no.14, S.1213-1215

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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.

Source

Information processing and management. 40(2004) no.3, S.515-526

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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.

Source

Journal of the American Society for Information Science and Technology. 57(2006) no.10, S.1303-1314

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Abstract

Web links have been studied by information scientists for at least six years but it is only in the past two that clear evidence has emerged to show that counts of links to scholarly Web spaces (universities and departments) can correlate significantly with research measures, giving some credence to their use for the investigation of scholarly communication. This paper reports an a study to investigate the factors that influence the creation of links to journal Web sites. An empirical approach is used: collecting data and testing for significant patterns. The specific questions addressed are whether site age and site content are inducers of links to a journal's Web site as measured by the ratio of link counts to Journal Impact Factors, two variables previously discovered to be related. A new methodology for data collection is also introduced that uses the Internet Archive to obtain an earliest known creation date for Web sites. The results show that both site age and site content are significant factors for the disciplines studied: library and information science, and law. Comparisons between the two fields also show disciplinary differences in Web site characteristics. Scholars and publishers should be particularly aware that richer content an a journal's Web site tends to generate links and thus the traffic to the site.

Source

Journal of the American Society for Information Science and technology. 54(2003) no.1, S.29-38

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Source

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

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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

Academic social network sites Academia.edu and ResearchGate, and reference sharing sites Mendeley, Bibsonomy, Zotero, and CiteULike, give scholars the ability to publicize their research outputs and connect with each other. With millions of users, these are a significant addition to the scholarly communication and academic information-seeking eco-structure. There is thus a need to understand the role that they play and the changes, if any, that they can make to the dynamics of academic careers. This article investigates attributes of philosophy scholars on Academia.edu, introducing a median-based, time-normalizing method to adjust for time delays in joining the site. In comparison to students, faculty tend to attract more profile views but female philosophers did not attract more profile views than did males, suggesting that academic capital drives philosophy uses of the site more than does friendship and networking. Secondary analyses of law, history, and computer science confirmed the faculty advantage (in terms of higher profile views) except for females in law and females in computer science. There was also a female advantage for both faculty and students in law and computer science as well as for history students. Hence, Academia.edu overall seems to reflect a hybrid of scholarly norms (the faculty advantage) and a female advantage that is suggestive of general social networking norms. Finally, traditional bibliometric measures did not correlate with any Academia.edu metrics for philosophers, perhaps because more senior academics use the site less extensively or because of the range informal scholarly activities that cannot be measured by bibliometric methods.

Source

Journal of the Association for Information Science and Technology. 65(2014) no.4, S.721-731

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Source

Information processing and management. 41(2005) no.6, S.1495-1510

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Source

Journal of the American Society for Information Science and technology. 54(2003) no.8, S.706-712

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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.

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Source

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

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Source

Online information review. 32(2008) no.1, S.89-101

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Journal of the American Society for Information Science and Technology. 60(2009) no.2, S.219-231

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Journal of the American Society for Information Science and Technology. 60(2009) no.12, S.2567-2576

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Journal of the American Society for Information Science and Technology. 64(2013) no.8, S.1608-1617

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