Key-feature analysis for dummies
A comprehensive step-by-step guide for novice researchers
DOI:
https://doi.org/10.14393/LL63-v42S-2026-12Keywords:
Register Analysis, Academic Writing, Key-feature Analysis, Statistics for novice researchers, Academic Writing IntroductionsAbstract
Corpus linguistics enriches academic writing instruction by comparing different text registers. This study presents a detailed guide to Key-Feature Analysis (KFA), a powerful methodology designed to identify both lexico-grammatical differences and similarities across texts. Recognizing that many linguistics students are deterred by complex statistics, this paper aims to make KFA more accessible. It provides a comprehensible explanation of the methodology, its calculations, and relevant software. To demonstrate its application, the study uses KFA to compare the introductions of academic articles and dissertations, written in English by academics and Brazilian graduate students, respectively. Key findings reveal that articles feature significantly more split auxiliaries and infinitives, which enables movements of persuasion and emphasis, while dissertations predominantly use demonstrative pronouns, which reveal a necessity of reference connections. Ultimately, this work seeks to empower students to confidently apply KFA in their own research.Downloads
References
BALLO, K.; PAULI, R.; WORRELL, M. Undergraduate students’ experiences of anxiety in statistics courses. Psychology Learning & Teaching, [S. l.], v. 9, n. 3, p. 274–285, 2016.
BIBER, D.; GRAY, B. Challenging stereotypes about academic writing: complexity, elaboration, and explicitness. Journal of English for Academic Purposes, [S. l.], v. 9, n. 1, p. 2–20, 2010.
BIBER, D. Variation across Speech and Writing. 1. ed., [s.l.] : Cambridge University Press, 1988. DOI: 10.1017/CBO9780511621024. Disponível em: https://www.cambridge.org/core/product/identifier/9780511621024/type/book. Acesso em: 8 jul. 2025.
BIBER, D.; CONRAD, S. Register, Genre, and Style. [s.l.] : Cambridge University Press, 2019. 423 p. Google-Books-ID: x7OQDwAAQBAJ.
BIBER, D.; CONRAD, S.; CORTES, V. If you look at …: Lexical Bundles in University Teaching and Textbooks. Applied Linguistics, [S. l.], v. 25, n. 3, p. 371–405, 2004. DOI: 10.1093/applin/25.3.371.
BIBER, D.; CONRAD, S.; REPPEN, R. Corpus Linguistics: Investigating Language Structure and Use. [s.l.] : Cambridge University Press, 1998. 324 p. Google-Books-ID: 2h5F7TXa6psC.
BRAGA, J.; MARQUES, C.; DUTRA, D.; TEIXEIRA, G.; OLIVEIRA, S. O Uso de Present Simple, Present Perfect, Past Simple e Past Perfect nas Introduções de Artigos Científicos, Teses e Dissertações Escritos em Inglês na Área de Ciências Agrárias. In: XVI Encontro de Linguística de Corpus e XIII Escola Brasileira de Linguística Computacional, 2024, Brasília. Anais eletrônicos [...] Associação Brasileira de Linguística de Corpus, 2024. p. 59 – 60. Disponível em: https://www.elc-ebralc.net.br/anais. Acesso em: 9 dez. 2025.
BREZINA, V. Statistics in Corpus Linguistics: A Practical Guide. Cambridge: Cambridge University Press, 2018. DOI: 10.1017/9781316410899. Disponível em: https://www.cambridge.org/core/books/statistics-in-corpus-linguistics/4E530F86B328B2287681AD240796D2CF. Acesso em: 8 jul. 2025.
CHEW, P.; DILLON, D. Statistics Anxiety Update: Refining the Construct and Recommendations for a New Research Agenda. Perspectives on Psychological Science, [S. l.], v. 9, n. 2, p. 196–208, 2014. DOI: 10.1177/1745691613518077.
COHEN, J. Statistical Power Analysis for the Behavioral Sciences. 2. ed., New York: Routledge, 2013. 567 p. DOI: 10.4324/9780203771587.
DUTRA, D.; BERBER SARDINHA, T. The role of Corpus Linguistics in EAP. Em: English For Academic Purposes: Reflections, Description & Pedagogy. 1. ed., Porto Alegre: Zouk, 2024.
DUTRA, D.; BOCORNY, A.; COSTA, D.; TEIXEIRA, G.; MARQUES, C. Desafios Metodológicos na Compilação de Textos Acadêmicos das Ciências Agrárias. In: XVI Encontro de Linguística de Corpus e XIII Escola Brasileira de Linguística Computacional, 2024, Brasília. Anais eletrônicos [...] Associação Brasileira de Linguística de Corpus, 2024. p. 39 – 40. Disponível em: https://www.elc-ebralc.net.br/anais. Acesso em: 9 dez. 2025.
DUTRA, D.; BOCORNY, A.; COSTA, D.; TEIXEIRA, G.; MARQUES, C. Introducing CROPS: A specialized corpus of Agrarian Sciences graduate theses from Brazilian universities. [S. l.], in preparation.
EGBERT, J.; BIBER, D. Key feature analysis: a simple, yet powerful method for comparing text varieties. Corpora, [S. l.], v. 18, n. 1, p. 121–133, 2023. DOI: 10.3366/cor.2023.0275.
FLOWERDEW, L. Corpus-based research and pedagogy in EAP: From lexis to genre. Language Teaching, [S. l.], v. 48, n. 1, p. 99–116, 2015. DOI: 10.1017/S0261444813000037.
GRIES, S. Quantitative Corpus Linguistics with R: A Practical Introduction. 2. ed., New York: Routledge, 2016. 286 p. DOI: 10.4324/9781315746210.
KITJAROENPAIBOON, W.; FAHKRAJANG, S.; FONGSARUN, P.; PLOYLERMSAENG, W. A Review of Lexico-grammatical Features and their Functions in an Academic Discourse. Journal of Multidisciplinary in Social Sciences, [S. l.], v. 19, n. 2, p. 99–112, 2023.
LARSON-HALL, J.; LARSON-HALL, J. A Guide to Doing Statistics in Second Language Research Using SPSS. New York: Routledge, 2009. 440 p. DOI: 10.4324/9780203875964.
LE FOLL, E.; SHAKIR, M. The Multi-Feature Tagger of English (MFTE): Rationale, description and evaluation. Research in Corpus Linguistics, [S. l.], v. 13, n. 2, p. 63–93, 2024. DOI: 10.32714/ricl.13.02.03.
MURTONEN, M.; LEHTINEN, E. Difficulties Experienced by Education and Sociology Students in Quantitative Methods Courses. Studies in Higher Education, [S. l.], v. 28, n. 2, p. 171–185, 2003. DOI: 10.1080/0307507032000058064.
NINI, A. MAT The Multidimensional-Analysis-Tagger. 2019. Disponível em: https://www.scribd.com/document/670853671/MAT-The-multidimensional-analysis-tagger. Acesso em: 30 jun. 2024.
O’KEEFFE, A.; MCCARTHY, M.; CARTER, R. From Corpus to Classroom: Language Use and Language Teaching. Cambridge: Cambridge University Press, 2007. (Cambridge Professional Learning). DOI: 10.1017/CBO9780511497650.
PLONSKY, L.; OSWALD, F. How Big Is “Big”? Interpreting Effect Sizes in L2 Research. Language Learning, [S. l.], v. 64, n. 4, p. 878–912, 2014. DOI: 10.1111/lang.12079.
QUIRK, R.; GREENBAUM, S.; LEECH, G.; SVARTIVIK, J. A grammar of contemporary English language. Harlow: Longman, 1985.
RAMOS, C.; OLIVEIRA, S.; DUTRA, D.; BRAGA, J.; VICTOR, A. Nominalization: Corpus-Based Study of Discussion Sections in Forestry Research Articles. In: XVI Encontro de Linguística de Corpus e XIII Escola Brasileira de Linguística Computacional, 2024, Brasília. Anais eletrônicos [...] Associação Brasileira de Linguística de Corpus, 2024. p. 53 – 54. Disponível em: https://www.elc-ebralc.net.br/anais. Acesso em: 9 dez. 2025.
RODMAN, L. The active voice in scientific articles: frequency and discourse functions. Journal of Technical Writing and Communication, [S. l.], v. 24, n. 3, p. 309–331, 1994.
SCOTT, M. PC analysis of key words — And key key words. System, [S. l.], v. 25, n. 2, p. 233–245, 1997. DOI: 10.1016/S0346-251X(97)00011-0.
SILVA, C.; BRITO, M.; CAZORLA, I.; VENDRAMINI, C. Atitudes em relação à estatística e à matemática. Psico-USF, [S. l.], v. 7, p. 219–228, 2002. DOI: 10.1590/S1413-82712002000200011.
SWALES, J.; FREAK, C. Academic Writing for Graduate Students: Essential Tasks and Skills. Ann Arbor: The University of Michigan Press, 2012.
TRIBBLE, C.; WINGATE, U. From text to corpus – A genre-based approach to academic literacy instruction. System, [S. l.], v. 41/1, n. 2, p. 307–321, 2013.
Downloads
Published
Issue
Section
Categories
License
Copyright (c) 2026 Carolina Grondona, Luciana Aguiar de Oliveira (Autor)

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
The authors retain author's rights but grant the journal the right of firsth publication. The works are licensed under Creative Commons Attribution License, which allows sharing provided that the authors and this journal are properly ackonwledged.






