scholarly journals The dispersion of the citation distribution of top scientists’ publications

2016 ◽  
Vol 109 (3) ◽  
pp. 1711-1724 ◽  
Author(s):  
Giovanni Abramo ◽  
Ciriaco Andrea D’Angelo ◽  
Anastasiia Soldatenkova
Keyword(s):  
Citation Distribution

scholarly journals Bibliometric analysis of multi-language veterinary journals

2017 ◽  
Vol 29 (3) ◽  
pp. 343-353
Author(s):  
Erwin KRAUSKOPF ◽  
Fernanda GARCIA ◽  
Robert FUNK
Keyword(s):  
Impact Factor ◽  
Bibliometric Analysis ◽  
Web Of Science ◽  
Country Of Origin ◽  
Citation Distribution ◽  
Journal Citation Reports ◽  
The Subject ◽  
Number Of Citations ◽  
The Impact ◽  
Main Language

Abstract The purpose of this study was to investigate the association between language and total number of citations found among documents in journals written in English and other languages. We selected all the journals clustered together in the Journal Citation Reports 2014 under the subject category “Veterinary Sciences” and downloaded all the data registered between 1994-2013 by Web of Science for the journals that stated publishing documents in languages other than English. We classified each of these journals by quartile and extracted information regarding their impact factor, language(s) stated, country of origin, total number of documents published, total number of reviews published, percentage of documents published in English and the quartile in which each journal ranked. Of the 48,118 documents published by the 28 journals analyzed, 55.8% were published in English. Interestingly, although most of the journals state being multi-language, most documents published in quartile 1 journals were in English (an average of 99.2%), while the percentage was 93.1% in quartile 2 journals, 62.1% in quartile 3 journals and 27.4% in quartile 4 journals. We also confirmed that citation distribution in these journals was highly skewed. The results of this study suggest that journals should consider adopting English as the main language as this will increase citation counts and the impact factor of the journal.

Ranking of finance journals: a stochastic dominance analysis

2016 ◽  
Vol 42 (4) ◽  
pp. 312-323 ◽  
Author(s):  
Erin H. Kao ◽  
Chuan-Hao Hsu ◽  
Yunlin Lu ◽  
Hung-Gay Fung
Keyword(s):  
Stochastic Dominance ◽  
Convincing Evidence ◽  
Research Quality ◽  
Journal Ranking ◽  
Citation Distribution ◽  
Dynamic Nature ◽  
Content Type ◽  
Clear Cut ◽  
Changes Over Time ◽  
Over Time

Purpose – Prior studies in citation-based journal rankings tend to be static to compare across journals. One journal may be judged better in citations than other journals at some points in time but not at the others. The assumption that the citation distribution is normally distributed and that the citation observations are independent and identically distributed (i.i.d.) may not be appropriate. The paper aims to discuss these issues. Design/methodology/approach – This study uses a stochastic dominance (SD) analysis, which overcomes the dynamic nature of changes in citation over time. The SD method proposed by Linton, Maasoumi, and Whang (hereafter LMW, 2005) does not require the data to be i.i.d. We use the LMW method to compare the relative ranking of 23 finance journals using citations for all articles from them during 1990-2010. Findings – The study indicates that the citation distribution changes over time. Thus a SD analysis is a better approach for a comparison of journal ranking. The findings unambiguously place JF, JFE, RFS, JFQA, and JFI in the top five spots of the finance journal ranking. The “near-top” journals, such as JBF, JCF, and FM, are not clear cut in the SD analysis. Research limitations/implications – The results confirm that ranking for the lower ranked journals may change over time especially, but the top three journals appear to be robust across methods and over time. Originality/value – The results of SD analysis provides more convincing evidence on finance journal ranking and could be useful to rank academic institutions, faculty research quality, and help the authors to decide what to read and which journals are influential.

The Dynamics Between Forward Citations and Price of Singleton Patents

2015 ◽  
Vol 12 (03) ◽  
pp. 1540003 ◽  
Author(s):  
Shyam Sreekumaran Nair ◽  
Mary Mathew
Keyword(s):  
Case Studies ◽  
Latent Variables ◽  
Market Price ◽  
Citation Distribution ◽  
Price Distribution ◽  
Auction Price ◽  
Business Practitioners ◽  
The Right ◽  
Forward Citations

In recent years, business practitioners are seen valuing patents on the basis of the market price that the patent can attract. Researchers have also looked into various patent latent variables and firm variables that influence the price of a patent. Forward citations of a patent are shown to play a role in determining price. Using patent auction price data (of Ocean Tomo now ICAP patent brokerage), we delve deeper into the role of forward citations. The successfully sold 167 singleton patents form the sample of our study. We found that, it is mainly the right tail of the citation distribution that explains the high prices of the patents falling on the right tail of the price distribution. There is consistency in the literature on the positive correlation between patent prices and forward citations. In this paper, we go deeper to understand this linear relationship through case studies. Case studies of patents with high and low citations are described in this paper to understand why some patents attracted high prices. We look into the role of additional patent latent variables like age, technology discipline, class and breadth of the patent in influencing citations that a patent receives.

Breadth and depth of citation distribution

2015 ◽  
Vol 51 (2) ◽  
pp. 130-140 ◽  
Author(s):  
Siluo Yang ◽  
Ruizhen Han
Keyword(s):  
Citation Distribution

Partitioning highly, medium and lowly cited publications

2020 ◽  
pp. 016555152091765
Author(s):  
Yong Huang ◽  
Yi Bu ◽  
Ying Ding ◽  
Wei Lu
Keyword(s):  
Web Of Science ◽  
Citation Distribution ◽  
Research Practices ◽  
Novel Approach

Dividing papers based on their numbers of citations into several groups constitutes one of the most common research practices in bibliometrics and beyond. However, existing dividing methods are both arbitrary and subject to bias. This article proposes a novel approach to partition highly, medium and lowly cited publications based on their citation distribution. We utilise the whole Web of Science (WoS) dataset to demonstrate how to apply this approach to scholarly datasets and examine the robustness of our algorithm in each of the six disciplines under the WoS dataset. The codes that underlie the algorithm are available online.

scholarly journals Central indexes to the citation distribution: a complement to the h-index

2011 ◽  
Vol 88 (3) ◽  
pp. 729-745 ◽  
Author(s):  
Pablo Dorta-González ◽  
María-Isabel Dorta-González
Keyword(s):  
Citation Distribution ◽  
H Index
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