Search (53 results, page 1 of 3)

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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

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Date

10. 1.1999 16:22:37

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Abstract

This is a practical guide to using web metrics to measure impact and demonstrate value. The web provides an opportunity to collect a host of different metrics, from those associated with social media accounts and websites to more traditional research outputs. This book is a clear guide for library and information professionals as to what web metrics are available and how to assess and use them to make informed decisions and demonstrate value. As individuals and organizations increasingly use the web in addition to traditional publishing avenues and formats, this book provides the tools to unlock web metrics and evaluate the impact of this content. The key topics covered include: bibliometrics, webometrics and web metrics; data collection tools; evaluating impact on the web; evaluating social media impact; investigating relationships between actors; exploring traditional publications in a new environment; web metrics and the web of data; the future of web metrics and the library and information professional. The book will provide a practical introduction to web metrics for a wide range of library and information professionals, from the bibliometrician wanting to demonstrate the wider impact of a researcher's work than can be demonstrated through traditional citations databases, to the reference librarian wanting to measure how successfully they are engaging with their users on Twitter. It will be a valuable tool for anyone who wants to not only understand the impact of content, but demonstrate this impact to others within the organization and beyond.

Content

1. Introduction. MetricsIndicators -- Web metrics and Ranganathan's laws of library science -- Web metrics for the library and information professional -- The aim of this book -- The structure of the rest of this book -- 2. Bibliometrics, webometrics and web metrics. Web metrics -- Information science metrics -- Web analytics -- Relational and evaluative metrics -- Evaluative web metrics -- Relational web metrics -- Validating the results -- 3. Data collection tools. The anatomy of a URL, web links and the structure of the web -- Search engines 1.0 -- Web crawlers -- Search engines 2.0 -- Post search engine 2.0: fragmentation -- 4. Evaluating impact on the web. Websites -- Blogs -- Wikis -- Internal metrics -- External metrics -- A systematic approach to content analysis -- 5. Evaluating social media impact. Aspects of social network sites -- Typology of social network sites -- Research and tools for specific sites and services -- Other social network sites -- URL shorteners: web analytic links on any site -- General social media impact -- Sentiment analysis -- 6. Investigating relationships between actors. Social network analysis methods -- Sources for relational network analysis -- 7. Exploring traditional publications in a new environment. More bibliographic items -- Full text analysis -- Greater context -- 8. Web metrics and the web of data. The web of data -- Building the semantic web -- Implications of the web of data for web metrics -- Investigating the web of data today -- SPARQL -- Sindice -- LDSpider: an RDF web crawler -- 9. The future of web metrics and the library and information professional. How far we have come -- The future of web metrics -- The future of the library and information professional and web metrics.

RSWK

Bibliothek / World Wide Web / World Wide Web 2.0 / Analyse / Statistik
Bibliometrie / Semantic Web / Soziale Software

Subject

Bibliothek / World Wide Web / World Wide Web 2.0 / Analyse / Statistik
Bibliometrie / Semantic Web / Soziale Software

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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

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Abstract

A substantial amount of research has focused on the persistence or availability of Web citations. The present study analyzes Web citation distributions. Web citations are defined as the mentions of the URLs of Web pages (Web resources) as references in academic papers. The present paper primarily focuses on the analysis of the URLs of Web citations and uses three sets of data, namely, Set 1 from the Humanities and Social Science Index in China (CSSCI, 1998-2009), Set 2 from the publications of two international computer science societies, Communications of the ACM and IEEE Computer (1995-1999), and Set 3 from the medical science database, MEDLINE, of the National Library of Medicine (1994-2006). Web citation distributions are investigated based on Web site types, Web page types, URL frequencies, URL depths, URL lengths, and year of article publication. Results show significant differences in the Web citation distributions among the three data sets. However, when the URLs of Web citations with the same hostnames are aggregated, the distributions in the three data sets are consistent with the power law (the Lotka function).

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Abstract

Changes in the topography of the Web can be expressed in at least four ways: (1) more sites on more servers in more places, (2) more pages and objects added to existing sites and pages, (3) changes in traffic, and (4) modifications to existing text, graphic, and other Web objects. This article does not address the first three factors (more sites, more pages, more traffic) in the growth of the Web. It focuses instead on changes to an existing set of Web documents. The article documents changes to an aging set of Web pages, first identified and "collected" in December 1996 and followed weekly thereafter. Results are reported through February 2001. The article addresses two related phenomena: (1) the life cycle of Web objects, and (2) changes to Web objects. These data reaffirm that the half-life of a Web page is approximately 2 years. There is variation among Web pages by top-level domain and by page type (navigation, content). Web page content appears to stabilize over time; aging pages change less often than once they did

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Abstract

This article argues that individual Web sites form hyperlink-affiliations with others for the purpose of strengthening their individual trust, expertness, and safety. It describes the hyperlink-affiliation network structure of Korea's top 152 Web sites. The data were obtained from their Web sites for October 2000. The results indicate that financial Web sites, such as credit card and stock Web sites, occupy the most central position in the network. A cluster analysis reveals that the structure of the hyperlink-affiliation network is influenced by the financial Web sites with which others are affiliated. These findings are discussed from the perspective of Web site credibility.

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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.

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Abstract

Vaughn, and Shaw look at the relationship between traditional citation and Web citation (not hyperlinks but rather textual mentions of published papers). Using English language research journals in ISI's 2000 Journal Citation Report - Information and Library Science category - 1209 full length papers published in 1997 in 46 journals were identified. Each was searched in Social Science Citation Index and on the Web using Google phrase search by entering the title in quotation marks, and followed for distinction where necessary with sub-titles, author's names, and journal title words. After removing obvious false drops, the number of web sites was recorded for comparison with the SSCI counts. A second sample from 1992 was also collected for examination. There were a total of 16,371 web citations to the selected papers. The top and bottom ranked four journals were then examined and every third citation to every third paper was selected and classified as to source type, domain, and country of origin. Web counts are much higher than ISI citation counts. Of the 46 journals from 1997, 26 demonstrated a significant correlation between Web and traditional citation counts, and 11 of the 15 in the 1992 sample also showed significant correlation. Journal impact factor in 1998 and 1999 correlated significantly with average Web citations per journal in the 1997 data, but at a low level. Thirty percent of web citations come from other papers posted on the web, and 30percent from listings of web based bibliographic services, while twelve percent come from class reading lists. High web citation journals often have web accessible tables of content.

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Abstract

Purpose - The essential purpose of this paper is to measure the amount of web resources used for scholarly contributions in the area of library and information science (LIS) in India. It further aims to make an analysis of the nature and type of web resources and studies the various standards for web citations. Design/methodology/approach - In this study, the result of analysis of 292 web citations spread over 95 scholarly papers published in the proceedings of the National Conference of the Society for Information Science, India (SIS-2005) has been reported. All the 292 web citations were scanned and data relating to types of web domains, file formats, styles of citations, etc., were collected through a structured check list. The data thus obtained were systematically analyzed, figurative representations were made and appropriate interpretations were drawn. Findings - The study revealed that 292 (34.88 per cent) out of 837 were web citations, proving a significant correlation between the use of Internet resources and research productivity of LIS professionals in India. The highest number of web citations (35.6 per cent) was from .edu/.ac type domains. Most of the web resources (46.9 per cent) cited in the study were hypertext markup language (HTML) files. Originality/value - The paper is the result of an original analysis of web citations undertaken in order to study the dependence of LIS professionals in India on web sources for their scholarly contributions. This carries research value for web content providers, authors and researchers in LIS.

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Abstract

This article explores the associations that message features and Web structural features have with perceptions of Web site credibility. In a within-subjects experiment, 84 participants actively located health-related Web sites an the basis of two tasks that differed in task specificity and complexity. Web sites that were deemed most credible were content analyzed for message features and structural features that have been found to be associated with perceptions of source credibility. Regression analyses indicated that message features predicted perceived Web site credibility for both searches when controlling for Internet experience and issue involvement. Advertisements and structural features had no significant effects an perceived Web site credibility. Institutionaffiliated domain names (.gov, org, edu) predicted Web site credibility, but only in the general search, which was more difficult. Implications of results are discussed in terms of online credibility research and Web site design.

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Abstract

This article addresses the question of whether the Web can serve as an information source for research. Specifically, it analyzes by way of content analysis the Web pages retrieved by the major search engines on a particular date (June 7, 1998), as a result of the query 'informetrics OR informetric'. In 807 out of the 942 retrieved pages, the search terms were mentioned in the context of information science. Over 70% of the pages contained only indirect information on the topic, in the form of hypertext links and bibliographical references without annotation. The bibliographical references extracted from the Web pages were analyzed, and lists of most productive authors, most cited authors, works, and sources were compiled. The list of reference obtained from the Web was also compared to data retrieved from commercial databases. For most cases, the list of references extracted from the Web outperformed the commercial, bibliographic databases. The results of these comparisons indicate that valuable, freely available data is hidden in the Web waiting to be extracted from the millions of Web pages

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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.

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Abstract

Recent Web-searching and -mining tools are combining text and link analysis to improve ranking and crawling algorithms. The central assumption behind such approaches is that there is a correiation between the graph structure of the Web and the text and meaning of pages. Here I formalize and empirically evaluate two general conjectures drawing connections from link information to lexical and semantic Web content. The link-content conjecture states that a page is similar to the pages that link to it, and the link-cluster conjecture that pages about the same topic are clustered together. These conjectures are offen simply assumed to hold, and Web search tools are built an such assumptions. The present quantitative confirmation sheds light an the connection between the success of the latest Web-mining techniques and the small world topology of the Web, with encouraging implications for the design of better crawling algorithms.

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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.

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Abstract

The number and type of Web citations to journal articles in four areas of science are examined: biology, genetics, medicine, and multidisciplinary sciences. For a sample of 5,972 articles published in 114 journals, the median Web citation counts per journal article range from 6.2 in medicine to 10.4 in genetics. About 30% of Web citations in each area indicate intellectual impact (citations from articles or class readings, in contrast to citations from bibliographic services or the author's or journal's home page). Journals receiving more Web citations also have higher percentages of citations indicating intellectual impact. There is significant correlation between the number of citations reported in the databases from the Institute for Scientific Information (ISI, now Thomson Scientific) and the number of citations retrieved using the Google search engine (Web citations). The correlation is much weaker for journals published outside the United Kingdom or United States and for multidisciplinary journals. Web citation numbers are higher than ISI citation counts, suggesting that Web searches might be conducted for an earlier or a more fine-grained assessment of an article's impact. The Web-evident impact of non-UK/USA publications might provide a balance to the geographic or cultural biases observed in ISI's data, although the stability of Web citation counts is debatable.

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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.

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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.

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Abstract

The study examined Web co-links to Canadian university Web sites. Multidimensional scaling (MDS) was used to analyze and visualize co-link data as was done in co-citation analysis. Co-link data were collected in ways that would reflect three different views, the global view, the French Canada view, and the English Canada view. Mapping results of the three data sets accurately reflected the ways Canadians see the universities and clearly showed the linguistic and cultural differences within Canadian society. This shows that Web co-linking is not a random phenomenon and that co-link data contain useful information for Web data mining. It is proposed that the method developed in the study can be applied to other contexts such as analyzing relationships of different organizations or countries. This kind of research is promising because of the dynamics and the diversity of the Web.

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Abstract

Because of the increasing presence of scientific publications an the Web, combined with the existing difficulties in easily verifying and retrieving these publications, research an techniques and methods for retrieval of scientific Web publications is called for. In this article, we report an the initial steps taken toward the construction of a test collection of scientific Web publications within the subject domain of plant biology. The steps reported are those of data gathering and data analysis aiming at identifying characteristics of scientific Web publications. The data used in this article were generated based an specifically selected domain topics that are searched for in three publicly accessible search engines (Google, AlITheWeb, and AItaVista). A sample of the retrieved hits was analyzed with regard to how various publication attributes correlated with the scientific quality of the content and whether this information could be employed to harvest, filter, and rank Web publications. The attributes analyzed were inlinks, outlinks, bibliographic references, file format, language, search engine overlap, structural position (according to site structure), and the occurrence of various types of metadata. As could be expected, the ranked output differs between the three search engines. Apparently, this is caused by differences in ranking algorithms rather than the databases themselves. In fact, because scientific Web content in this subject domain receives few inlinks, both AItaVista and AlITheWeb retrieved a higher degree of accessible scientific content than Google. Because of the search engine cutoffs of accessible URLs, the feasibility of using search engine output for Web content analysis is also discussed.