An Analysis of Fifty Citation Superstars from the Scientific Literature

1992 ◽  
Vol 22 (1) ◽  
pp. 17-37 ◽  
Author(s):  
Joseph E. Harmon

This article contains results from a literary analysis of fifty scientific papers selected from the top 100 most-cited papers appearing in the Science Citation Index for the period 1945–1988. Most papers are from the field of biochemistry and became citation superstars because their authors discovered a method or material that numerous others could use in their own research. The typical paper has two authors, two tables, six figures, and twenty-two references. It adheres to the conventional topical organization, with the topics distributed as follows: 2 percent abstract, 5 percent introduction, 25 percent methods and materials, 50 percent results, 10 percent discussion, 4 percent conclusion, and 4 percent reference list. Tables and figures occupy about 30 percent of the article. With respect to the writing style, the average sentence is somewhat long (24 words) but not unreasonably so, and the sentence structure is simple greater than half the time. Moreover, sentences tend to rely heavily on to be verbs (about 80% of sentences have at least one) and abstract nouns (0.66 per sentence). Explanations for the typical form and writing style in these papers are provided.

Cephalalgia ◽  
2016 ◽  
Vol 37 (13) ◽  
pp. 1299-1309 ◽  
Author(s):  
Claude Robert ◽  
Concepción S Wilson ◽  
Richard B Lipton ◽  
Charles-Daniel Arreto

Aim This study charts the growth of the scientific journal literature on headache for 30+ years (1983–2014). Methods Using the Web of Science, articles published in four two-year periods (1983–1984, 1993–1994, 2003–2004, 2013–2014) from journals indexed in the Science Citation Index Expanded database were retrieved and analyzed. Results From 1983–1984 to 2013–2014, the scientific literature on headache increased nearly fourfold (3.8) from 468 to 1776 articles; the number of participating countries more than doubled (26 to 67); and the two most prolific countries in each period were the USA and Italy. While several European countries (Italy, Germany, UK and Denmark) were among the top 10 in each period, the notable appearance of Turkey, China and Brazil among the top 10 in 2013–2014 indicates the growing geographic spread of publications on headache research. Meanwhile, the comet-like distribution of journals has not changed: two journals, Headache and Cephalalgia, persist throughout as the nucleus, with the tail increasing more than threefold from 141 journals in 1983–1984 to 462 in 2013–2014. Conclusion Our study follows the recent growth and spread of the scientific literature on headache research and should stimulate further bibliometric investigation in this field.


1992 ◽  
Vol 22 (4) ◽  
pp. 357-375 ◽  
Author(s):  
Joseph E. Harmon

This article discusses the typical form and content of forty theoretical scientific papers. These papers were chosen from the 400 most-cited papers in the Science Citation Index for the period 1945–1988 (reported by Eugene Garfield in a series of recent essays appearing in Current Contents). It was found that the typical form for these papers is similar to that for experimental and methods papers, but the content differs substantially. In brief, the content follows the logical sequence: problem or need, assumptions made in attempting to solve problem or meet need, theorem derived from those assumptions and additional considerations, proof of theorem by logical reasoning or validation by comparison with what is established or establishable, conclusions from previous discussion, and recommendations on future experimental or theoretical work. Also, compared with experimental and methods papers, these theoretical papers have somewhat fewer figures and tables, but many more references and equations.


2021 ◽  
pp. 1-38
Author(s):  
Josh M. Nicholson ◽  
Milo Mordaunt ◽  
Patrice Lopez ◽  
Ashish Uppala ◽  
Dominic Rosati ◽  
...  

Abstract Citation indices are tools used by the academic community for research and research evaluation which aggregate scientific literature output and measure impact by collating citation counts. Citation indices help measure the interconnections between scientific papers but fall short because they fail to communicate contextual information about a citation. The usage of citations in research evaluation without consideration of context can be problematic, because a citation that presents contrasting evidence to a paper is treated the same as a citation that presents supporting evidence. To solve this problem, we have used machine learning, traditional document ingestion methods, and a network of researchers to develop a “smart citation index” called scite, which categorizes citations based on context. Scite shows how a citation was used by displaying the surrounding textual context from the citing paper and a classification from our deep learning model that indicates whether the statement provides supporting or contrasting evidence for a referenced work, or simply mentions it. Scite has been developed by analyzing over 25 million full-text scientific articles and currently has a database of more than 880 million classified citation statements. Here we describe how scite works and how it can be used to further research and research evaluation. Peer Review https://publons.com/publon/10.1162/qss_a_00146


2021 ◽  
Author(s):  
Joshua M Nicholson ◽  
Milo Mordaunt ◽  
Patrice Lopez ◽  
Ashish Uppala ◽  
Domenic Rosati ◽  
...  

Citation indices are tools used by the academic community for research and research evaluation which aggregate scientific literature output and measure scientific impact by collating citation counts. Citation indices help measure the interconnections between scientific papers but fall short because they only display paper titles, authors, and the date of publications, and fail to communicate contextual information about why a citation was made. The usage of citations in research evaluation without due consideration to context can be problematic, if only because a citation that disputes a paper is treated the same as a citation that supports it. To solve this problem, we have used machine learning and other techniques to develop a "smart citation index" called scite, which categorizes citations based on context. Scite shows how a citation was used by displaying the surrounding textual context from the citing paper, and a classification from our deep learning model that indicates whether the statement provides supporting or disputing evidence for a referenced work, or simply mentions it. Scite has been developed by analyzing over 23 million full-text scientific articles and currently has a database of more than 800 million classified citation statements. Here we describe how scite works and how it can be used to further research and research evaluation.


2020 ◽  
Vol 210 ◽  
pp. 18065
Author(s):  
Olga Fedotova ◽  
Vladimir Latun

The article analyzes the state and level of theoretical elaboration of the issues of pedagogy of the postmodern era in the Russian scientific literature. Based on the analysis of the content of publications posted in the Russian leading bibliographic resource - bibliographic database of scientific publications “The Russian Science Citation Index» – the ratio of publications devoted to the problems of postmodernism in non-pedagogical and pedagogical discourse is revealed. There are established the main clusters, which include publications on general problems of postmodern pedagogy, problems of meta-postmodern pedagogy and anti-pedagogy. The interpretive approach allows us to prove that in Russian pedagogy, critical and analytical consideration of foreign pedagogical arrays dominates. At the same time, there are first attempts to determine the author's position on the creation of Russian postmodern pedagogy, which at present is not completely methodologically entrusted. The arguments used by the authors to substantiate postmodern pedagogy are very exotic and fully correspond to the principle “Anything goes”, which is a methodologically regulating postmodern pedagogy.


2016 ◽  
Vol 5 (6) ◽  
pp. 3-15
Author(s):  
Девисилов ◽  
Vladimir Devisilov

Scientometrical indicators for scientist activity, scientific magazines, citation indexes, methods of their definition and work with them have been considered. Main bases for scientific data – Scopus, Web of Science, Russian index of scientific citation (Russian science citation index) have been presented, rules of their use and work with them. Merits and demerits of the main scientometrical indicators are analyzed and recommendations for increase of scientist citation index are given. Scientific article’s structure, as well as requirements to its basic elements influencing a paper’s citation level, have been explained, recommendations for preparation of such paper’s basic elements as its heading, abstract, keywords, citable sources’ bibliography have been given. The structure for the paper’s main text has been considered and recommendations on its writing have been given. A conclusion is drawn that one of the reasons related to low level citation of Russian scientists, and references to publications in Russian magazines is a lack of culture in writing of scientific papers and not observance of their preparation rules that complicates their annotation in bases of scientific data.


2013 ◽  
pp. 129-146 ◽  
Author(s):  
N. Kurakova ◽  
L. Tsvetkova ◽  
O. Eremchenko

The paper analyses the publications of Russian authors in various fields of economics indexed in Web of Science and Russian Science Citation Index. The authors claim that the scientometric parameters are only in a limited way applicable in evaluating the performance of expert and thesis boards in economics in Russia. The authors also put forward the approaches in order to improve Russia’s positions in the international citations indexes in economics.


Author(s):  
Nikolay Mazov ◽  
◽  
Vadim Gureyev ◽  
◽  
◽  
...  

Twenty two science Russian periodicals in informatics and library studies are selected for the bibliometrical analysis of key journal indicators, including publication activity of the same journals’ editorial staff. For the first time for domestic journals, the study reveals hidden self-citation when editorial members include links to their journal from other publications. The available instruments of scientometrical databases, including Web of Science and Scopus, and the national system Russian Science Citation Index do not enable to identify this form of self-citation. The mentioned manipulations are aimed at boosting journal rating. In several cases, intensive and unjustified citation by journals’ editorial staff in other periodicals which we consider the violation of publication ethical principles, is revealed.


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