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Examining scientific writing styles from the perspective of linguistic complexity

Author

Listed:
  • Chao Lu
  • Yi Bu
  • Jie Wang
  • Ying Ding
  • Vetle Torvik
  • Matthew Schnaars
  • Chengzhi Zhang

Abstract

Publishing articles in high‐impact English journals is difficult for scholars around the world, especially for non‐native English‐speaking scholars (NNESs), most of whom struggle with proficiency in English. To uncover the differences in English scientific writing between native English‐speaking scholars (NESs) and NNESs, we collected a large‐scale data set containing more than 150,000 full‐text articles published in PLoS between 2006 and 2015. We divided these articles into three groups according to the ethnic backgrounds of the first and corresponding authors, obtained by Ethnea, and examined the scientific writing styles in English from a two‐fold perspective of linguistic complexity: (a) syntactic complexity, including measurements of sentence length and sentence complexity; and (b) lexical complexity, including measurements of lexical diversity, lexical density, and lexical sophistication. The observations suggest marginal differences between groups in syntactical and lexical complexity.

Suggested Citation

  • Chao Lu & Yi Bu & Jie Wang & Ying Ding & Vetle Torvik & Matthew Schnaars & Chengzhi Zhang, 2019. "Examining scientific writing styles from the perspective of linguistic complexity," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 70(5), pages 462-475, May.
    • Handle: RePEc:bla:jinfst:v:70:y:2019:i:5:p:462-475
    DOI: 10.1002/asi.24126
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    Citations

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    Cited by:

    1. Kun Sun & Haitao Liu & Wenxin Xiong, 2021. "The evolutionary pattern of language in scientific writings: A case study of Philosophical Transactions of Royal Society (1665–1869)," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 1695-1724, February.
    2. Song, Ningyuan & Chen, Kejun & Zhao, Yuehua, 2023. "Understanding writing styles of scientific papers in the IS-LS domain: Evidence from abstracts over the past three decades," Journal of Informetrics, Elsevier, vol. 17(1).
    3. Lu, Chao & Bu, Yi & Dong, Xianlei & Wang, Jie & Ding, Ying & Larivière, Vincent & Sugimoto, Cassidy R. & Paul, Logan & Zhang, Chengzhi, 2019. "Analyzing linguistic complexity and scientific impact," Journal of Informetrics, Elsevier, vol. 13(3), pages 817-829.
    4. Bikun Chen & Dannan Deng & Zhouyan Zhong & Chengzhi Zhang, 2020. "Exploring linguistic characteristics of highly browsed and downloaded academic articles," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(3), pages 1769-1790, March.
    5. Gui Wang & Hui Wang & Xinyi Sun & Nan Wang & Li Wang, 2023. "Linguistic complexity in scientific writing: A large-scale diachronic study from 1821 to 1920," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(1), pages 441-460, January.
    6. Chen, Liang & Xu, Shuo & Zhu, Lijun & Zhang, Jing & Yang, Guancan & Xu, Haiyun, 2022. "A deep learning based method benefiting from characteristics of patents for semantic relation classification," Journal of Informetrics, Elsevier, vol. 16(3).
    7. van den Besselaar, Peter & Mom, Charlie, 2022. "The effect of writing style on success in grant applications," Journal of Informetrics, Elsevier, vol. 16(1).
    8. Amon, Julian & Hornik, Kurt, 2022. "Is it all bafflegab? – Linguistic and meta characteristics of research articles in prestigious economics journals," Journal of Informetrics, Elsevier, vol. 16(2).
    9. Shuo Xu & Ling Li & Xin An & Liyuan Hao & Guancan Yang, 2021. "An approach for detecting the commonality and specialty between scientific publications and patents," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(9), pages 7445-7475, September.
    10. Lu, Wei & Liu, Zhifeng & Huang, Yong & Bu, Yi & Li, Xin & Cheng, Qikai, 2020. "How do authors select keywords? A preliminary study of author keyword selection behavior," Journal of Informetrics, Elsevier, vol. 14(4).

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