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Axiomatic characterisation of a bibliometric index provides insight into the properties that the index satisfies and facilitates the comparison of different indices. A geometric generalisation of the $h$-index, called the $\chi$-index, has recently been proposed to address some of the problems with the $h$-index, in particular, the fact that it is not scale invariant, i.e., multiplying the number of citations of each publication by a positive constant may change the relative ranking of two researchers. While the square of the $h$-index is the area of the largest square under the citation curve of a researcher, the square of the $\chi$-index, which we call the $rec$-index (or {\em rectangle}-index), is the area of the largest rectangle under the citation curve. Our main contribution here is to provide a characterisation of the $rec$-index via three properties: {\em monotonicity}, {\em uniform citation} and {\em uniform equivalence}. Monotonicity is a natural property that we would expect any bibliometric index to satisfy, while the other two properties constrain the value of the $rec$-index to be the area of the largest rectangle under the citation curve. The $rec$-index also allows us to distinguish between {\em influential} researchers who have relatively few, but highly-cited, publications and {\em prolific} researchers who have many, but less-cited, publications., Comment: 14 pages, 3 figures. This is a pre-print of an article published in Scientometrics. The final authenticated version is available online at: https://doi.org/10.1007/s11192-019-03151-7

This panel brings together experts in bibliometrics and information retrieval to discuss how each of these two important areas of information science can help to inform the research of the other. There is a growing body of literature that capitalizes on the synergies created by combining methodological approaches of each to solve research problems and practical issues related to how information is created, stored, organized, retrieved and used. The session will begin with an overview of the common threads that exist between IR and metrics, followed by a summary of findings from the BIR workshops and examples of research projects that combine aspects of each area to benefit IR or metrics research areas, including search results ranking, semantic indexing and visualization. The panel will conclude with an engaging discussion with the audience to identify future areas of research and collaboration., Comment: 4 pages, accepted at the 2016 Annual Meeting of the Association for Information Science and Technology (ASIST 2016) in Copenhagen

In this paper we present "citation success index", a metric for comparing the citation capacity of pairs of journals. Citation success index is the probability that a random paper in one journal has more citations than a random paper in another journal (50% means the two journals do equally well). Unlike the journal impact factor (IF), the citation success index depends on the broadness and the shape of citation distributions. Also, it is insensitive to sporadic highly-cited papers that skew the IF. Nevertheless, we show, based on 16,000 journals containing ~2.4 million articles, that the citation success index is a relatively tight function of the ratio of IFs of journals being compared, due to the fact that journals with same IF have quite similar citation distributions. The citation success index grows slowly as a function of IF ratio. It is substantial (>90%) only when the ratio of IFs exceeds ~6, whereas a factor of two difference in IF values translates into a modest advantage for the journal with higher IF (index of ~70%). We facilitate the wider adoption of this metric by providing an online calculator that takes as input parameters only the IFs of the pair of journals.

A new methodology is proposed for comparing Google Scholar (GS) with other citation indexes. It focuses on the coverage and citation impact of sources, indexing speed, and data quality, including the effect of duplicate citation counts. The method compares GS with Elsevier's Scopus, and is applied to a limited set of articles published in 12 journals from six subject fields, so that its findings cannot be generalized to all journals or fields. The study is exploratory, and hypothesis generating rather than hypothesis-testing. It confirms findings on source coverage and citation impact obtained in earlier studies. The ratio of GS over Scopus citation varies across subject fields between 1.0 and 4.0, while Open Access journals in the sample show higher ratios than their non-OA counterparts. The linear correlation between GS and Scopus citation counts at the article level is high: Pearson's R is in the range of 0.8-0.9. A median Scopus indexing delay of two months compared to GS is largely though not exclusively due to missing cited references in articles in press in Scopus. The effect of double citation counts in GS due to multiple citations with identical or substantially similar meta-data occurs in less than 2 per cent of cases. Pros and cons of article-based and what is termed as concept-based citation indexes are discussed., Comment: Version 26 April 2016 accepted for publication in Journal of Informetrics

Altmetrics, indices based on social media platforms and tools, have recently emerged as alternative means of measuring scholarly impact. Such indices assume that scholars in fact populate online social environments, and interact with scholarly products there. We tested this assumption by examining the use and coverage of social media environments amongst a sample of bibliometricians. As expected, coverage varied: 82% of articles published by sampled bibliometricians were included in Mendeley libraries, while only 28% were included in CiteULike. Mendeley bookmarking was moderately correlated (.45) with Scopus citation. Over half of respondents asserted that social media tools were affecting their professional lives, although uptake of online tools varied widely. 68% of those surveyed had LinkedIn accounts, while Academia.edu, Mendeley, and ResearchGate each claimed a fifth of respondents. Nearly half of those responding had Twitter accounts, which they used both personally and professionally. Surveyed bibliometricians had mixed opinions on altmetrics' potential; 72% valued download counts, while a third saw potential in tracking articles' influence in blogs, Wikipedia, reference managers, and social media. Altogether, these findings suggest that some online tools are seeing substantial use by bibliometricians, and that they present a potentially valuable source of impact data., Comment: 12 pages, 6 figures. Accepted to 14th International Society of Scientometrics and Informatics Conference, Vienna Austria 15-19th July 2013

We propose a new index, the $j$-index, which is defined for an author as the sum of the square roots of the numbers of citations to each of the author's publications. The idea behind the $j$-index it to remedy a drawback of the $h$-index $-$ that the $h$-index does not take into account the full citation record of a researcher. The square root function is motivated by our desire to avoid the possible bias that may occur with a simple sum when an author has several very highly cited papers. We compare the $j$-index to the $h$-index, the $g$-index and the total citation count for three subject areas using several association measures. Our results indicate that that the association between the $j$-index and the other indices varies according to the subject area. One explanation of this variation may be due to the proportion of citations to publications of the researcher that are in the $h$-core. The $j$-index is {\em not} an $h$-index variant, and as such is intended to complement rather than necessarily replace the $h$-index and other bibliometric indicators, thus providing a more complete picture of a researcher's achievements., Comment: 12 pages

Our system illustrates how information retrieved from social networks can be used for suggesting experts for specific tasks. The system is designed to facilitate the task of finding the appropriate person(s) for a job, as a conference committee member, an advisor, etc. This short description will demonstrate how the system works in the context of the HCIR2012 published tasks., Comment: Participated in HCIR 2012

Traditionally, scholarly impact and visibility have been measured by counting publications and citations in the scholarly literature. However, increasingly scholars are also visible on the Web, establishing presences in a growing variety of social ecosystems. But how wide and established is this presence, and how do measures of social Web impact relate to their more traditional counterparts? To answer this, we sampled 57 presenters from the 2010 Leiden STI Conference, gathering publication and citations counts as well as data from the presenters' Web "footprints." We found Web presence widespread and diverse: 84% of scholars had homepages, 70% were on LinkedIn, 23% had public Google Scholar profiles, and 16% were on Twitter. For sampled scholars' publications, social reference manager bookmarks were compared to Scopus and Web of Science citations; we found that Mendeley covers more than 80% of sampled articles, and that Mendeley bookmarks are significantly correlated (r=.45) to Scopus citation counts., Comment: Accepted to 17th International Conference on Science and Technology Indicators, Montreal, Canada, 5-8 Sept. 2012. 14 pages, 3 figures, 3 tables

The opening book is an important component of a chess engine, and thus computer chess programmers have been developing automated methods to improve the quality of their books. For chess, which has a very rich opening theory, large databases of high-quality games can be used as the basis of an opening book, from which statistics relating to move choices from given positions can be collected. In order to find out whether the opening books used by modern chess engines in machine versus machine competitions are ``comparable'' to those used by chess players in human versus human competitions, we carried out analysis on 26 test positions using statistics from two opening books one compiled from humans' games and the other from machines' games. Our analysis using several nonparametric measures, shows that, overall, there is a strong association between humans' and machines' choices of opening moves when using a book to guide their choices., Comment: 12 pages, 1 figure, 6 tables

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 about 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., Comment: 19 pages, 4 figures, 8 tables

Reviews the literature on the use of Web search engines in information science research, including: ways users interact with Web search engines; social aspects of searching; structure and dynamic nature of the Web; link analysis; other bibliometric applications; characterizing information on the Web; search engine evaluation and improvement; and clustering, classification, ranking, and filtering. (Contains 199 references.) (MES)

Presents a selective review of research based on the Internet, using bibliometric and informetric methods and tools. Highlights include data collection methods on the Internet, including surveys, logging, and search engines; and informetric analysis, including citation analysis and content analysis. (Contains 78 references.) (Author/LRW)