本文对国际科学计量学杂志《Ｓｃｉｅｎｔｏｍｅｔｒｉｃｓ》１９７９－１９９１年的研究论文内容、栏目、作者及国别和编委及国别作了计量分析，揭示出科学计量学研究的重点、活动的中心及发展趋势，说明了学科带头人在发展科学计量学这门新兴学科中的作用。

国际刊物《Scientometrics》文献计量研究

Google Scholar, Web of Science, and Scopus: A systematic comparison of citations in 252 subject categories

Despite citation counts from Google Scholar (GS), Web of Science (WoS), and Scopus being widely consulted by researchers and sometimes used in research evaluations, there is no recent or systematic evidence about the differences between them. In response, this paper investigates 2,448,055 citations to 2,299 English-language highly-cited documents from 252 GS subject categories published in 2006, comparing GS, the WoS Core Collection, and Scopus. GS consistently found the largest percentage of citations across all areas (93%-96%), far ahead of Scopus (35%-77%) and WoS (27%-73%). GS found nearly all the WoS (95%) and Scopus (92%) citations. Most citations found only by GS were from non-journal sources (48%-65%), including theses, books, conference papers, and unpublished materials. Many were non-English (19%-38%), and they tended to be much less cited than citing sources that were also in Scopus or WoS. Despite the many unique GS citing sources, Spearman correlations between citation counts in GS and WoS or Scopus are high (0.78-0.99). They are lower in the Humanities, and lower between GS and WoS than between GS and Scopus. The results suggest that in all areas GS citation data is essentially a superset of WoS and Scopus, with substantial extra coverage.

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Google Scholar, Web of Science, and Scopus: a systematic comparison of citations in 252 subject categories

Rigorous evidence identification is essential for systematic reviews and meta-analyses (evidence syntheses) because the sample selection of relevant studies determines a review's outcome, validity, and explanatory power. Yet, the search systems allowing access to this evidence provide varying levels of precision, recall, and reproducibility and also demand different levels of effort. To date, it remains unclear which search systems are most appropriate for evidence synthesis and why. Advice on which search engines and bibliographic databases to choose for systematic searches is limited and lacking systematic, empirical performance assessments. This study investigates and compares the systematic search qualities of 28 widely used academic search systems, including Google Scholar, PubMed, and Web of Science. A novel, query-based method tests how well users are able to interact and retrieve records with each system. The study is the first to show the extent to which search systems can effectively and efficiently perform (Boolean) searches with regards to precision, recall, and reproducibility. We found substantial differences in the performance of search systems, meaning that their usability in systematic searches varies. Indeed, only half of the search systems analyzed and only a few Open Access databases can be recommended for evidence syntheses without adding substantial caveats. Particularly, our findings demonstrate why Google Scholar is inappropriate as principal search system. We call for database owners to recognize the requirements of evidence synthesis and for academic journals to reassess quality requirements for systematic reviews. Our findings aim to support researchers in conducting better searches for better evidence synthesis.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/jrsm.1378

Which Academic Search Systems are Suitable for Systematic Reviews or Meta‐Analyses? Evaluating Retrieval Qualities of Google Scholar, PubMed and 26 other Resources

Information on the size of academic search engines and bibliographic databases (ASEBDs) is often outdated or entirely unavailable. Hence, it is difficult to assess the scope of specific databases, such as Google Scholar. While scientometric studies have estimated ASEBD sizes before, the methods employed were able to compare only a few databases. Consequently, there is no up-to-date comparative information on the sizes of popular ASEBDs. This study aims to fill this blind spot by providing a comparative picture of 12 of the most commonly used ASEBDs. In doing so, we build on and refine previous scientometric research by counting query hit data as an indicator of the number of accessible records. Iterative query optimization makes it possible to identify a maximum number of hits for most ASEBDs. The results were validated in terms of their capacity to assess database size by comparing them with official information on database sizes or previous scientometric studies. The queries used here are replicable, so size information can be updated quickly. The findings provide first-time size estimates of ProQuest and EbscoHost and indicate that Google Scholar’s size might have been underestimated so far by more than 50%. By our estimation Google Scholar, with 389 million records, is currently the most comprehensive academic search engine.

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Google Scholar to overshadow them all? Comparing the sizes of 12 academic search engines and bibliographic databases

Suitability of Google Scholar as a source of scientific information and as a source of data for scientific evaluation—Review of the Literature

This article introduces the Multidimensional Research Assessment Matrix of scientific output. Its base notion holds that the choice of metrics to be applied in a research assessment process depends on the unit of assessment, the research dimension to be assessed, and the purposes and policy context of the assessment. An indicator may by highly useful within one assessment process, but less so in another. For instance, publication counts are useful tools to help discriminate between those staff members who are research active, and those who are not, but are of little value if active scientists are to be compared with one another according to their research performance. This paper gives a systematic account of the potential usefulness and limitations of a set of 10 important metrics, including altmetrics, applied at the level of individual articles, individual researchers, research groups, and institutions. It presents a typology of research impact dimensions and indicates which metrics are the most appropriate to measure each dimension. It introduces the concept of a “meta-analysis” of the units under assessment in which metrics are not used as tools to evaluate individual units, but to reach policy inferences regarding the objectives and general setup of an assessment process.

Multidimensional assessment of scholarly research impact

This study examines the nature of citations to articles that were retracted in 2014. Out of 987 retracted articles found in ScienceDirect, an Elsevier full text database, we selected all articles that received more than 10 citations between January 2015 and March 2016. Since the retraction year was known for only about 83% of the retracted articles, we chose to concentrate on recent citations, that for certain appeared after the cited paper was retracted. Overall, we analyzed 238 citing documents and identified the context of each citation as positive, negative or neutral. Our results show that the vast majority of citations to retracted articles are positive despite of the clear retraction notice on the publisher's platform and regardless of the reason for retraction. Positive citations can be also seen to articles that were retracted due to ethical misconduct, data fabrication and false reports. In light of these results, we listed some recommendations for publishers that could potentially minimize the referral to retracted studies as valid.

/pdf/post-retraction-citations-in-context-a-case-study-2riawpnn7p.pdf

Post retraction citations in context: a case study.

A bibliometric approach is explored to tracking international scientific migration, based on an analysis of the affiliation countries of authors publishing in peer reviewed journals indexed in Scopus. The paper introduces a model that relates base concepts in the study of migration to bibliometric constructs, and discusses the potentialities and limitations of a bibliometric approach both with respect to data accuracy and interpretation. Synchronous and asynchronous analyses are presented for 10 rapidly growing countries and 7 scientifically established countries. Rough error rates of the proposed indicators are estimated. It is concluded that the bibliometric approach is promising provided that its outcomes are interpreted with care, based on insight into the limits and potentialities of the approach, and combined with complementary data, obtained, for instance, from researchers' Curricula Vitae o, survey or questionnaire- based data. Error rates for units of assessment with indicator values based on sufficiently large numbers are estimated to be fairly below 10 %, but can be expected to vary substantially among countries of origin, especially between Asian countries and Western countries.

Gali Halevi

Papers

Suitability of Google Scholar as a source of scientific information and as a source of data for scientific evaluation—Review of the Literature

Multidimensional assessment of scholarly research impact

Post retraction citations in context: a case study.

A bibliometric approach to tracking international scientific migration

A new methodology for comparing Google Scholar and Scopus