In this study we carried out a content analysis of Web pages containing the search term "S&T indicators", which were located by an extensive search of the Web. Our results clearly show that the Web is a valuable information source on this topic. Major national and international institutions and organizations publish the full text of their reports on the Web, or allow free downloading of these reports in non-html formats. In addition to direct information, a number of pages listing and linking to major reports, programs and organizations were also located.
The impact factor is one of the most used scientometric indicators. Its proper and improper uses have been discussed extensively before. It has been criticized extensively, yet it is still here. In this paper I propose the journal report card, which is a set of measures, each with an easily comprehensible meaning that provides a fuller picture of the journals’ standing. The set of measures in the report card include the impact factor, the h-index, number of citations at different points on the ranked list of citations, extent of uncitedness and coverage of the h-core. The report card is computed for two sets of journals, the top-20 journals in JCR 2010 and the top-20 journals in JCR 2010 for the category Information and Library Science.
Links analysis proved to be very fruitful on the Web. Google's very successful ranking algorithm is based on link analysis. There are only a few studies that analyzed links qualitatively, most studies are quantitative. Our purpose was to characterize these links in order to gain a better understanding why links are created. We limited the study to the academic environment, and as a specific case we chose to characterize the interlinkage between the eight Israeli universities.
We present different methods of data collection from the Web for informetric purposes. For each method, some studies utilizing it are reviewed, and advantages and shortcomings of each technique are discussed. The paper emphasizes that data collection must be carried out with great care. Since the Web changes constantly, the findings of any study are valid only in the time frame in which it was carried out, and are dependent on the quality of the data collection tools, which are usually not under the control of the researcher. At the current time, the quality and the reliability of most of the available search tools are not satisfactory, thus informetric analyses of the Web mainly serve as demonstrations of the applicability of informetric methods to this medium, and not as a means for obtaining definite conclusions. A possible solution is for the scientific world to develop its own search and data collection tools.
In September 2008 Thomson Reuters added to the ISI Web of Science (WOS) the Conference Proceedings Citation Indexes for Science
and for the Social Sciences and Humanities. This paper examines how this change affects the publication and citation counts
of highly cited computer scientists. Computer science is a field where proceedings are a major publication venue. The results
show that most of the highly cited publications of the sampled researchers are journal publications, but these highly cited
items receive more than 40% of their citations from proceedings papers. The paper also discusses issues related to double-counting,
i.e., when a given work is published both in a proceedings and later on as a journal paper.
In this paper we investigate the retrieval capabilities of six Internet search engines on a simple query. As a case study
the query “Erdos” was chosen. Paul Erdos was a world famous Hungarian mathematician, who passed away in September 1996. Existing
work on search engine evaluation considers only the first ten or twenty results returned by the search engine, therefore approximation
of the recalls of the engines has not been considered so far. In this work we retrieved all 6681 documents that the search
engines pointed at and thoroughly examined them. Thus we could calculate the precision of the whole retrieval process, study
the overlap between the results of the engines and give an estimate on the recall of the searches. The precision of the engines
is high, recall in very low and the overlap is minimal.
In this paper we introduce two measures self-linked and self-linkingthat are the analogues of self-citing and self-cited rates for scientific journals. These rates are calculated for a sample of sites to assess their meaning and utility. Self-linked is the more meaningful measure for the sample sites. As a first step towards a better understanding of self-linking (linking within a site), a sample of pages from an academic site was characterized using the method of content analysis. Even though most of the links serve navigational or other technical purposes, the percentage of content-bearing links among the self-links is significant, and even the portion of research oriented links is non-negligible.
Paul Erdos was a world famous Hungarian mathematician, who passed away in September 1996. Documents on the World Wide Web,
mentioning Paul Erdos's name were systematically collected. These documents were categorized using the method of content analysis.
This work enables us to draw some conclusions about the ways authors of Internet documents picture Paul Erdos. This is the
first work we know of that thoroughly examines the content of a huge collection of documents on a specific topic on the Internet.
In this paper we examine the applicability of the concept of h-index to topics, where a topic has index h, if there are h publications that received at least h citations and the rest of the publications on the topic received at most h citations. We discuss methodological issues related to the computation of h-index of topics (denoted h-b index by BANKS ). Data collection for computing the h-b index is much more complex than computing the index for authors, research groups and/or journals, and has several limitations.
We demonstrate the methods on a number of informetric topics, among them the h-index.