Formulating rules to identify key researchers in computer science : A quantitative approach

Web of Science (WoS) and Google Scholar (GS) are prominent citation services with distinct indexing mechanisms. Comprehensive knowledge about the growth patterns of these two citation services is lacking. We analyzed the development of citation counts in WoS and GS for two classic articles and 56 articles from diverse research fields, making a distinction between retroactive growth (i.e., the relative difference between citation counts up to mid-2005 measured in mid-2005 and citation counts up to mid-2005 measured in April 2013) and actual growth (i.e., the relative difference between citation counts up to mid-2005 measured in April 2013 and citation counts up to April 2013 measured in April 2013). One of the classic articles was used for a citation-by-citation analysis. Results showed that GS has substantially grown in a retroactive manner (median of 170 % across articles), especially for articles that initially had low citations counts in GS as compared to WoS. Retroactive growth of WoS was small, with a median of 2 % across articles. Actual growth percentages were moderately higher for GS than for WoS (medians of 54 vs. 41 %). The citation-by-citation analysis showed that the percentage of citations being unique in WoS was lower for more recent citations (6.8 % for citations from 1995 and later vs. 41 % for citations from before 1995), whereas the opposite was noted for GS (57 vs. 33 %). It is concluded that, since its inception, GS has shown substantial expansion, and that the majority of recent works indexed in WoS are now also retrievable via GS. A discussion is provided on quantity versus quality of citations, threats for WoS, weaknesses of GS, and implications for literature research and research evaluation.

Objective – To determine whether three competing citation tracking services result in differing citation counts for a known set of articles, and to assess the extent of any differences.
 
 Design – Citation analysis, observational study.
 
 Setting – Three citation tracking databases: Google Scholar, Scopus and Web of Science.
 
 Subjects – Citations from eleven journals each from the disciplines of oncology and condensed matter physics for the years 1993 and 2003.
 
 Methods – The researchers selected eleven journals each from the list of journals from Journal Citation Reports 2004 for the categories “Oncology” and “Condensed Matter Physics” using a systematic sampling technique to ensure journals with varying impact factors were included. All references from these 22 journals were retrieved for the years 1993 and 2003 by searching three databases: Web of Science, INSPEC, and PubMed. Only research articles were included for the purpose of the study. From these, a stratified random sample was created to proportionally represent the content of each journal (oncology 1993: 234 references, 2003: 259 references; condensed matter physics 1993: 358 references, 2003: 364 references). In November of 2005, citations counts were obtained for all articles from Web of Science, Scopus and Google Scholar. Due to the small sample size and skewed distribution of data, non-parametric tests were conducted to determine whether significant differences existed between sets.
 
 Main results – For 1993, mean citation counts were highest in Web of Science for both oncology (mean = 45.3, SD = 77.4) and condensed matter physics (mean = 22.5, SD = 32.5). For 2003, mean citation counts were higher in Scopus for oncology (mean = 8.9, SD = 12.0), and in Web of Science for condensed matter physics (mean = 3.0, SD = 4.0). There was not enough data for the set of citations from Scopus for condensed matter physics for 1993 and it was therefore excluded from analysis. A Friedman test to measure for differences between all remaining groups suggested a significant difference existed, and so pairwise post-hoc comparisons were performed. The Wilcoxon Signed Ranked tests demonstrated significant differences “in citation counts between all pairs (p < 0.001) except between Google Scholar and Scopus for CM physics 2003 (p = 0.119).” 
 
 The study also looked at the number of unique references from each database, as well as the proportion of overlap for the 2003 citations. In the area of oncology, there was found to be 31% overlap between databases, with Google Scholar including the most unique references (13%), followed by Scopus (12%) and Web of Science (7%). For condensed matter physics, the overlap was lower at 21% and the largest number of unique references was found in Web of Science (21%), with Google Scholar next largest (17%) and Scopus the least (9%). Citing references from Google Scholar were found to originate from not only journals, but online archives, academic repositories, government and non-government white papers and reports, commercial organizations, as well as other sources.
 
 Conclusion – The study does not confirm the authors’ hypothesis that differing scholarly coverage would result in different citation counts from the three databases. While there were significant differences in mean citation rates between all pairs of databases except for Google Scholar and Scopus in condensed matter physics for 2003, no one database performed better overall. Different databases performed better for different subjects, as well as for different years, especially Scopus, which only includes references starting in 1996. The results of this study suggest that the best citation database will depend on the years being searched as well as the subject area. For a complete picture of citation behaviour, the authors suggest all three be used.

Quality and quantity are not always positively correlated: A case study of Chinese economics journals

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

AimsHow often a medical article is cited is important for many people because it is used to calculate different variables such as the h‐index and the journal impact factor. The aim of this analysis was to assess how the citation count varies between Web of Science (WoS), Scopus, and Google Scholar in the current literature.MethodsWe included the top 50 cited articles of four journals ESC Heart Failure; Journal of cachexia, sarcopenia and muscle; European Journal of Preventive Cardiology; and European Journal of Heart Failure in our analysis that were published between 1 January 2016 and 10 October 2019. We recorded the number of citations of these articles according to WoS, Scopus, and Google Scholar on 10 October 2019.ResultsThe top 50 articles in ESC Heart Failure were on average cited 12 (WoS), 13 (Scopus), and 17 times (Google Scholar); in Journal of cachexia, sarcopenia and muscle 37 (WoS), 43 (Scopus), and 60 times (Google Scholar); in European Journal of Preventive Cardiology 41 (WoS), 56 (Scopus), and 67 times (Google Scholar); and in European Journal of Heart Failure 76 (WoS), 108 (Scopus), and 230 times (Google Scholar). On average, the top 50 articles in all four journals were cited 41 (WoS), 52 (Scopus, 26% higher citations count than WoS, range 8–42% in the different journals), and 93 times (Google Scholar, 116% higher citation count than WoS, range 42–203%).ConclusionScopus and Google Scholar on average have a higher citation count than WoS, whereas the difference is much larger between Google Scholar and WoS.

This paper presents a current overview of the main productive and influential countries around the world in the computer science field. Research in the computer science field has experienced significant growth in recent years. This study develops a bibliometric overview of all journals that have been indexed in the Web of Science (WoS) database over the past 25 years (1995–2019), according to several bibliometric indicators in the seven categories of computer science research. The study shows that United States is the leading country in the computer science field. Other countries, such as the United Kingdom, China, Canada and Germany, also obtain high positions in the ranking. The average country that performs research in computer science is European, has English-speaking researchers, is highly developed and has a high income. However, there is a wide range of countries that perform research in computer science, including South American and Arabic countries, meaning that computer science traverses many countries and cultures.

PurposeThe purpose of this paper is to analyse the publications of, and the citations to, the current staff of 19 departments of computer science in Malaysian universities, and to compare these bibliometric data with expert peer reviews of Malaysian research performance.Design/methodology/approachThis paper searches citation of the Scopus and Web of Science databases.FindingsBoth publication and citation rates are low, although this is at least in part due to some Malaysian universities having only a teaching function. More of the departments' publications were identified in Scopus than in Web of Science, but both databases were needed for comprehensive coverage. Statistically significant relationships were observed between the departments' publication and citation counts and the rankings of the departments' parent universities in two evaluations of the research performance of Malaysian universities.Originality/valueThis is the first comparison of bibliometric and peer‐review data for Malaysia, and, more generally, for a country with a newly developed higher education system.

Learning How to Believe: Epistemic Development in Cultural Context

To identify and analyse the main features of the top 100 most-cited randomized controlled trials, systematic reviews and meta-analyses published in endodontic journals from 1961 to 2018. The Clarivate Analytics' Web of Science 'All Databases' was used to search and analyse the 100 most frequently cited randomized controlled trials, systematic reviews and meta-analyses having 'randomized', 'randomised', 'randomized controlled', 'randomised controlled', 'randomized controlled trial', 'randomized controlled trials', 'clinical trial', 'systematic', 'systematic review', 'meta-analysis', and 'meta-analyses' in the title section. The 'International Endodontic Journal', 'Journal of Endodontics', 'Oral Surgery Oral Medicine Oral Pathology Oral Radiology and Endodontology', 'Australian Endodontic Journal', 'Endodontics & Dental Traumatology', 'Endo-Endodontic Practice Today' and 'European Endodontic Journal' were included in the publication name section. After ranking the articles in a descending order based on their citation counts, each article was cross-matched with the citation counts in Elsevier's Scopus and Google Scholar. The articles were analysed, and information on citation counts, citation density, year of publication, contributing authors, institutions and countries, journal of publication, study design, topic of the article and keywords was extracted. The citation counts of the 100 most-cited articles varied from 235 to 20 (Web of Science), 276 to 17 (Scopus) and 696 to 1 (Google Scholar). The year in which the top 100 articles were published was 2010 (n=13). Among 373 authors, the greatest number of articles was associated with three individuals namely Reader A (n=5), Beck M (n=5) and Kvist T (n=5). Most of the articles originated from the United States (n=24) with the greatest contribution from Ohio State University (USA) (n=5). Randomized controlled trials were the most frequent study design (n=45) followed by systematic reviews (n=30) with outcome studies of root canal treatment being the major topic (n=35). The Journal of Endodontics published the largest number of included articles (n=70) followed by the International Endodontic Journal (n=27). Among 259 unique keywords, meta-analysis (n=23) and systematic review (n=23) were the most frequently used. This study has revealed that year of publication had no obvious impact on citation count. The bibliometric analysis highlighted the quantity and quality of research, and the evolution of scientific advancements made in the field of Endodontology over time. Articles before 1996, that is prior to the CONSORT statement that encouraged authors to include specific terms in the title and keywords, may not have been included in this electronic search.

To analyze the 2007 citation count of articles published by the Croatian Medical Journal in 2005-2006 based on data from the Web of Science, Scopus, and Google Scholar. Web of Science and Scopus were searched for the articles published in 2005-2006. As all articles returned by Scopus were included in Web of Science, the latter list was the sample for further analysis. Total citation counts for each article on the list were retrieved from Web of Science, Scopus, and Google Scholar. The overlap and unique citations were compared and analyzed. Proportions were compared using chi(2)-test. Google Scholar returned the greatest proportion of articles with citations (45%), followed by Scopus (42%), and Web of Science (38%). Almost a half (49%) of articles had no citations and 11% had an equal number of identical citations in all 3 databases. The greatest overlap was found between Web of Science and Scopus (54%), followed by Scopus and Google Scholar (51%), and Web of Science and Google Scholar (44%). The greatest number of unique citations was found by Google Scholar (n=86). The majority of these citations (64%) came from journals, followed by books and PhD theses. Approximately 55% of all citing documents were full-text resources in open access. The language of citing documents was mostly English, but as many as 25 citing documents (29%) were in Chinese. Google Scholar shares a total of 42% citations returned by two others, more influential, bibliographic resources. The list of unique citations in Google Scholar is predominantly journal based, but these journals are mainly of local character. Citations received by internationally recognized medical journals are crucial for increasing the visibility of small medical journals but Google Scholar may serve as an alternative bibliometric tool for an orientational citation insight.

Neural coding.

Predictors of Citations in Neurosurgical Research: A 5-Year Follow-Up

The retraction of research papers, for whatever reason, is a growing phenomenon. However, although retracted paper information is publicly available via publishers, it is somewhat distributed and inconsistent. The aim is to assess: (i) the extent and nature of retracted research in Computer Science (CS) (ii) the post-retraction citation behaviour of retracted works and (iii) the potential impact upon systematic reviews and mapping studies. We analyse the Retraction Watch database and take citation information from the Web of Science and Google scholar. We find that of the 33,955 entries in the Retraction watch database (16 May 2022), 2,816 are classified as CS, i.e., ≈ 8%. For CS, 56% of retracted papers provide little or no information as to the reasons. This contrasts with 26% for other disciplines. There is also some disparity between different publishers, a tendency for multiple versions of a retracted paper to be available beyond the Version of Record (VoR), and for new citations long after a paper is officially retracted (median = 3; maximum = 18). Systematic reviews are also impacted with ≈ 30% of the retracted papers having one or more citations from a review. Unfortunately, retraction seems to be a sufficiently common outcome for a scientific paper that we as a research community need to take it more seriously, e.g., standardising procedures and taxonomies across publishers and the provision of appropriate research tools. Finally, we recommend particular caution when undertaking secondary analyses and meta-analyses which are at risk of becoming contaminated by these problem primary studies.

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Impact Factors and Other Measures of a Journal's Influence