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Language use reflects scientific methodology: A corpus-based study of peer-reviewed journal articles

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  • Shlomo Argamon

    (Illinois Institute of Technology Chicago)

  • Jeff Dodick

    (The Hebrew University of Jerusalem)

  • Paul Chase

    (Illinois Institute of Technology Chicago)

Abstract

Recently, philosophers of science have argued that the epistemological requirements of different scientific fields lead necessarily to differences in scientific method. In this paper, we examine possible variation in how language is used in peer-reviewed journal articles from various fields to see if features of such variation may help to elucidate and support claims of methodological variation among the sciences. We hypothesize that significant methodological differences will be reflected in related differences in scientists’ language style. This paper reports a corpus-based study of peer-reviewed articles from twelve separate journals in six fields of experimental and historical sciences. Machine learning methods were applied to compare the discourse styles of articles in different fields, based on easily-extracted linguistic features of the text. Features included function word frequencies, as used often in computational stylistics, as well as lexical features based on systemic functional linguistics, which affords rich resources for comparative textual analysis. We found that indeed the style of writing in the historical sciences is readily distinguishable from that of the experimental sciences. Furthermore, the most significant linguistic features of these distinctive styles are directly related to the methodological differences posited by philosophers of science between historical and experimental sciences, lending empirical weight to their contentions.

Suggested Citation

  • Shlomo Argamon & Jeff Dodick & Paul Chase, 2008. "Language use reflects scientific methodology: A corpus-based study of peer-reviewed journal articles," Scientometrics, Springer;Akadémiai Kiadó, vol. 75(2), pages 203-238, May.
    • Handle: RePEc:spr:scient:v:75:y:2008:i:2:d:10.1007_s11192-007-1768-y
    DOI: 10.1007/s11192-007-1768-y
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    References listed on IDEAS

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    1. Shlomo Argamon & Casey Whitelaw & Paul Chase & Sobhan Raj Hota & Navendu Garg & Shlomo Levitan, 2007. "Stylistic text classification using functional lexical features," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(6), pages 802-822, April.
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    Cited by:

    1. Amnah Alluqmani & Lior Shamir, 2018. "Writing styles in different scientific disciplines: a data science approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(2), pages 1071-1085, May.
    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. Adel Daoud & Sebastian Kohl, 2015. "Is there a New Economic Sociology Effect? A Topic Model on the Economic Orientation of Sociology, 1890 to 2014," Working Papers 1520, New School for Social Research, Department of Economics.
    4. Daoud, Adel & Kohl, Sebastian, 2016. "How much do sociologists write about economic topics? Using big data to test some conventional views in economic sociology, 1890 to 2014," MPIfG Discussion Paper 16/7, Max Planck Institute for the Study of Societies.
    5. 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).
    6. Henry Small, 2011. "Interpreting maps of science using citation context sentiments: a preliminary investigation," Scientometrics, Springer;Akadémiai Kiadó, vol. 87(2), pages 373-388, May.

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