Exploring linguistic characteristics of highly browsed and downloaded academic articles

Bikun Chen (), Dannan Deng, Zhouyan Zhong and Chengzhi Zhang
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Bikun Chen: Nanjing University of Science and Technology
Dannan Deng: Nanjing University of Science and Technology
Zhouyan Zhong: Nanjing University of Science and Technology
Chengzhi Zhang: Nanjing University of Science and Technology

Scientometrics, 2020, vol. 122, issue 3, No 23, 1769-1790

Abstract: Abstract Views and downloads of academic articles have become important supplementary indicators of scholarly impact. It is assumed that linguistic characteristics have an influence on article views and downloads to some extent. To understand the relationship between linguistic characteristics and article views and downloads, this study selected 63,002 full-text articles published from 2014 to 2015 in the PLoS (Public Library of Science) journals (PLoS Biology, PLoS Computational Biology, PLoS Genetics, PLoS Medicine, PLoS Neglected Tropical Diseases, PLoS One and PLoS Pathogens), and introduced seven indicators (title length, abstract length, full text length, sentence length, lexical diversity, lexical density and lexical sophistication) to measure linguistic characteristics of articles, grouped into Top 20% viewed and downloaded (proxy of highly browsed and downloaded articles), total and Bottom 20% viewed and downloaded categories. The results suggested that most linguistic characteristics played little role in article views and downloads in our data sets in general, but some linguistic characteristics (e.g. title length and average sentence length) in specific PLoS journal and platform (PLoS platform or PubMed Central platform) played certain role in article views and downloads. Also, journal differences and platform differences regarding linguistic characteristics of highly viewed and downloaded articles were existed.

Keywords: Linguistic characteristics; Linguistic complexity; Usage metrics; PLoS; PubMed Central; 91C99 (search for similar items in EconPapers)
JEL-codes: C80 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (10)

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DOI: 10.1007/s11192-020-03361-4

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