Judit Bar-Ilan

Which h-index? — A comparison of WoS, Scopus and Google Scholar

This paper compares the h-indices of a list of highly-cited Israeli researchers based on citations counts retrieved from the Web of Science, Scopus and Google Scholar respectively. In several case the results obtained through Google Scholar are considerably different from the results based on the Web of Science and Scopus. Data cleansing is discussed extensively.

Informetrics at the beginning of the 21st century—A review

This paper reviews developments in informetrics between 2000 and 2006. At the beginning of the 21st century we witness considerable growth in webometrics, mapping and visualization and open access. A new topic is comparison between citation databases, as a result of the introduction of two new citation databases Scopus and Google Scholar. There is renewed interest in indicators as a result of the introduction of the h-index. Traditional topics like citation analysis and informetric theory also continue to develop. The impact factor debate, especially outside the informetric literature continues to thrive. Ranked lists (of journal, highly cited papers or of educational institutions) are of great public interest.

Non-cryptographic fault-tolerant computing in constant number of rounds of interaction

Let ~(zI,... ,zn) be computed by a circuit C with bounded fanin. There are non-cryptographic protocols (BGW88,CCD88] by which a network of n processors can evaluate C at secret inputs Xl,,. >xn, revealing the final value f(x1,. . . ,x,,) without revealing any information about the inputs except what the final result provides. Current methods require O(depth(C)) rounds of communication and messages of size polynomial in size(C) and n. In practical terms, such a degree of interaction is unacceptable. We show how to secretly evaluate any finite function in a constant expected number of rounds, regardless of the minimal depth of a circuit for that function. We provide a means to simulate unbounded fanin multiplicative (or AND) gates using constant rounds. Using our new methods, any function can be evaluated in a constant number of rounds, using messages of size proportional to the size of a constant-depth, unbounded-fanin circuit describing the function. We also show how to secretly evaluate any function described by an algebraic formula of polynomial size (or an NC1 circuit), using a constant number of rounds yet requiring messages of only polynomial size. This provides a speedup over original methods by a factor of log n, while incurring only a polynomial number of bits. ‘This research was supported in part under NSF grant CCR-870-4513. Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the ACM copyright notice and the title of the publication and its date appear, and notice is given that copying is by permission of the Association for Computing Machinery. To copy otherwise, or to republish, requires a fee and/or specific permission. ?fll ii.,,

Comparing university rankings

Recently there is increasing interest in university rankings. Annual rankings of world universities are published by QS for the Times Higher Education Supplement, the Shanghai Jiao Tong University, the Higher Education and Accreditation Council of Taiwan and rankings based on Web visibility by the Cybermetrics Lab at CSIC. In this paper we compare the rankings using a set of similarity measures. For the rankings that are being published for a number of years we also examine longitudinal patterns. The rankings limited to European universities are compared to the ranking of the Centre for Science and Technology Studies at Leiden University. The findings show that there are reasonable similarities between the rankings, even though each applies a different methodology. The biggest differences are between the rankings provided by the QS-Times Higher Education Supplement and the Ranking Web of the CSIC Cybermetrics Lab. The highest similarities were observed between the Taiwanese and the Leiden rankings from European universities. Overall the similarities are increased when the comparison is limited to the European universities.

Methods for comparing rankings of search engine results

In this paper we present a number of measures that compare rankings of search engine results. We apply these measures to five queries that were monitored daily for two periods of 14 or 21 days each. Rankings of the different search engines (Google, Yahoo! and Teoma for text searches and Google, Yahoo! and Picsearch for image searches) are compared on a daily basis, in addition to longitudinal comparisons of the same engine for the same query over time. The results and rankings of the two periods are compared as well.

How to Allocate Network Centers

This paper deals with the issue of allocating and utilizing centers in a distributed network, in its various forms. The paper discusses the significant parameters of center allocation, defines the resulting optimization problems, and proposes several approximation algorithms for selecting centers and for distributing the users among them. We concentrate mainly on balanced versions of the problem, i.e., in which it is required that the assignment of clients to centers be as balanced as possible. The main results are constant ratio approximation algorithms for the balanced ?-centers and balanced ?-weighted centers problems, and logarithmic ratio approximation algorithms for the ?-dominating set and the k-tolerant set problems.

Data collection methods on the Web for infometric purposes — A review and analysis

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.

Do blog citations correlate with a higher number of future citations? Research blogs as a potential source for alternative metrics

Journal‐based citations are an important source of data for impact indices. However, the impact of journal articles extends beyond formal scholarly discourse. Measuring online scholarly impact calls for new indices, complementary to the older ones. This article examines a possible alternative metric source, blog posts aggregated at ResearchBlogging.org, which discuss peer‐reviewed articles and provide full bibliographic references. Articles reviewed in these blogs therefore receive “blog citations.” We hypothesized that articles receiving blog citations close to their publication time receive more journal citations later than the articles in the same journal published in the same year that did not receive such blog citations. Statistically significant evidence for articles published in 2009 and 2010 support this hypothesis for seven of 12 journals (58%) in 2009 and 13 of 19 journals (68%) in 2010. We suggest, based on these results, that blog citations can be used as an alternative metric source.

Research Blogs and the Discussion of Scholarly Information

The research blog has become a popular mechanism for the quick discussion of scholarly information. However, unlike peer-reviewed journals, the characteristics of this form of scientific discourse are not well understood, for example in terms of the spread of blogger levels of education, gender and institutional affiliations. In this paper we fill this gap by analyzing a sample of blog posts discussing science via an aggregator called ResearchBlogging.org (RB). ResearchBlogging.org aggregates posts based on peer-reviewed research and allows bloggers to cite their sources in a scholarly manner. We studied the bloggers, blog posts and referenced journals of bloggers who posted at least 20 items. We found that RB bloggers show a preference for papers from high-impact journals and blog mostly about research in the life and behavioral sciences. The most frequently referenced journal sources in the sample were: Science, Nature, PNAS and PLoS One. Most of the bloggers in our sample had active Twitter accounts connected with their blogs, and at least 90% of these accounts connect to at least one other RB-related Twitter account. The average RB blogger in our sample is male, either a graduate student or has been awarded a PhD and blogs under his own name.

Citations to the “Introduction to informetrics” indexed by WOS, Scopus and Google Scholar

Google Scholar and Scopus are recent rivals to Web of Science. In this paper we examined these three citation databases through the citations of the book “Introduction to informetrics” by Leo Egghe and Ronald Rousseau. Scopus citations are comparable to Web of Science citations when limiting the citation period to 1996 and onwards (the citation coverage of Scopus)—each database covered about 90% of the citations located by the other. Google Scholar missed about 30% of the citations covered by Scopus and Web of Science (90 citations), but another 108 citations located by Google Scholar were not covered either by Scopus or by Web of Science. Google Scholar performed considerably better than reported in previous studies, however Google Scholar is not very “user-friendly” as a bibliometric data collection tool at this point in time. Such “microscopic” analysis of the citing documents retrieved by each of the citation databases allows us a deeper understanding of the similarities and the differences between the databases.