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- In this post, we provide empirical insights into the value of Crossref as a new source of citation data. We compare Crossref with WoS and Scopus, focusing on the citation data that is available in the different data sources. Our analysis will show that more than three-quarters of the references in WoS and more than two-thirds of the Scopus references can be found in Crossref, with about half of these references being openly available. On the other hand, it will also be shown that millions of references are missing in Crossref. These references occur in publications that have been deposited in Crossref without their references.
- Databases provide citation counts and other metrics across a range of disciplines. No database has complete coverage of all publications. It is important to check their scope and use multiple sources to accurately represent your citation impact.
- Emerging metrics based on article-level does not exclude traditional metrics based on citations to the journal, but complements them. Both can be employed in conjunction to offer a richer picture of an article use from immediate to long terms. Article-level metrics (ALM) is the result of the aggregation of different data sources and the collection of content from multiple social network services. Sources used for the aggregation can be broken down into five categories: usage, captures, mentions, social media and citations. Data sources depend on the tool, but they include classic metrics indicators based on citations, academic social networks (Mendeley, CiteULike, Delicious) and social media (Facebook, Twitter, blogs, or Youtube, among others). Altmetrics is not synonymous with alternative metrics. Altmetrics are normally early available and allow to assess the social impact of scholarly outputs, almost at the real time. This paper overviews briefly the meaning of altmetrics and describes some of the existing tools used to apply this new metrics: Public Library of Science - Article-Level Metrics, Altmetric, Impactstory and Plum.
- Altmetric measurements derived from the social web are increasingly advocated and used as early indicators of article impact and usefulness. Nevertheless, there is a lack of systematic scientific evidence that altmetrics are valid proxies of either impact or utility although a few case studies have reported medium correlations between specific altmetrics and citation rates for individual journals or fields. Finally, the coverage of all the altmetrics except for Twitter seems to be low and so it is not clear if they are prevalent enough to be useful in practice.
- The small size of institutes and publication clusters is a problem when determining citation indices. To improve the citation indexing of small sets of publications (less than 50 or 100 publications), a method is proposed. In addition, a method for error calculation is given for large sets of publications. Here, the classical methods of citation indexing remain valid.
- The development of science with a rapid increase in the number of scientific researches, scientists and researchers, and the advent of novel scientific disciplines have led to an exponential rise in the number of journals, books, congress proceedings, dissertations, patents, technical reports and other publications bringing research results. These publications are referred to as primary publications or primary sources of information, pointing to the original character of the information presented. Convenient search of such a huge number of publications issued in different countries, in different languages and stored in different media would be impossible without special aids, i.e. secondary publications or secondary information sources, which process, analyze and summarize primary publications and help in their target search. As such a great amount of publications and their authors require proper evaluation, these secondary sources of information are al- so used for scientific validation, based on the high criteria they employ in the selection of primary publications to be systematically followed and processed.
- For more than 40 years, the Institute for Scientific Information (ISI, now part of Thomson-Reuters), produced the only available database making possible citation analysis, the Web of Science (WoS). Now, another company, Reed-Elsevier, has created its own bibliographic database, Scopus, available since 2002. For those who perform bibliometric analysis and comparisons of countries or institutions, the existence of these two major databases raises the important question of the comparability and stability of rankings obtained from different data sources
- Researchers turn to citation tracking to find the most influential articles for a particular topic and to see how often their own published papers are cited. For years researchers looking for this type of information had only one resource to consult: the Web of Science from Thomson Scientific. In 2004 two competitors emerged – Scopus from Elsevier and Google Scholar from Google. The research reported here uses citation analysis in an observational study examining these three databases; comparing citation counts for articles from two disciplines (oncology and condensed matter physics) and two years (1993 and 2003) to test the hypothesis that the different scholarly publication coverage provided by the three search tools will lead to different citation counts from each. Eleven journal titles with varying impact factors were selected from each discipline (oncology and condensed matter physics) using the Journal Citation Reports (JCR). All articles published in the selected titles were retrieved for the years 1993 and 2003, and a stratified random sample of articles was chosen, resulting in four sets of articles. During the week of November 7–12, 2005, the citation counts for each research article were extracted from the three sources. The actual citing references for a subset of the articles published in 2003 were also gathered from each of the three sources. For oncology 1993 Web of Science returned the highest average number of citations, 45.3. Scopus returned the highest average number of citations (8.9) for oncology 2003. Web of Science returned the highest number of citations for condensed matter physics 1993 and 2003 (22.5 and 3.9 respectively). The data showed a significant difference in the mean citation rates between all pairs of resources except between Google Scholar and Scopus for condensed matter physics 2003. For articles published in 2003 Google Scholar returned the largest amount of unique citing material for oncology and Web of Science returned the most for condensed matter physics. This study did not identify any one of these three resources as the answer to all citation tracking needs. Scopus showed strength in providing citing literature for current (2003) oncology articles, while Web of Science produced more citing material for 2003 and 1993 condensed matter physics, and 1993 oncology articles. All three tools returned some unique material. Our data indicate that the question of which tool provides the most complete set of citing literature may depend on the subject and publication year of a given article.
- Citation analysis was traditionally based on data from the ISI Citation indexes. Now with the appearance of Scopus, and with the free citation tool Google Scholar methods and measures are need for comparing these tools. In this paper we propose a set of measures for computing the similarity between rankings induced by ordering the retrieved publications in decreasing order of the number of citations as reported by the specific tools. The applicability of these measures is demonstrated and the results show high similarities between the rankings of the ISI Web of Science and Scopus and lower similarities between Google Scholar and the other tools.
publications (hide)41
- (2020)
- Journal of General Internal Medicine, 34 (6): 825--827 (Jun 1, 2019)
- (2019)
- Scientometrics, 114 (3): 1251-1273 (2018)
- Journal of the Association for Information Science and Technology, 67 (11): 2573-2828. (2016)
- (2016)
- Journal of the Association for Information Science and Technology, 67 (11): 2778--2789 (2016)
- Journal of the Association for Information Science and Technology, 67 (2): 91-112 (2016)
- (2016)
- JASIST, 67 (11): 2778-2789 (2016)
- (2016)
- (2016)
- (2016)
- (2015)
- (2015)
- (2014)
- Scientometrics, 98 (2): 1547-1565 (2014)
- (2014)
- (March 2013)
- CoRR, (2013)
