Abstract
The methodological debates surrounding keyword analysis have given rise to a wide range of keyness metrics. The present paper delineates four dimensions of keyness, which distinguish between frequency- and dispersion-related perspectives. Existing measures are then organized according to these dimensions and evaluated with regard to their performance on a specific keyword analysis task: The identification of key verbs in academic writing. To this end, the rankings produced by 32 different metrics are evaluated against an established academic word list. Further, the reliability of measures is assessed, to determine whether they produce stable rankings across repeated studies on the same pair of text varieties. We observe notable differences among metrics with regard to these criteria. Our findings provide further support for the superiority of the Wilcoxon rank sum test and text-dispersion–based measures, and allow us to identify, within each dimension of keyness, metrics that may be given preference in applied work.
Acknowledgements
I would like to thank the five anonymous reviewers for their constructive and helpful comments on earlier versions of this paper.
References
Baker, Paul. 2004. Querying keywords: Questions in difference, frequency, and sense in keyword analysis. Journal of English Linguistics 32(4). 346–359. https://doi.org/10.1177/0075424204269894.Suche in Google Scholar
Baroni, Marco & Stefan Evert. 2009. Statistical methods for corpus exploitation. In Anke Lüdeling & Merja Kytö (eds.), Corpus linguistics: An international handbook, 777–803. Berlin: Mouton de Gruyter.10.1515/9783110213881.2.777Suche in Google Scholar
Bestgen, Yves. 2014. Inadequacy of the chi-squared test to examine vocabulary differences between corpora. Literary and Linguistic Computing 29(2). 164–170. https://doi.org/10.1093/llc/fqt020.Suche in Google Scholar
Brezina, Vaclav & Miriam Meyerhoff. 2014. Significant or random? A critical review of sociolinguistic generalisations based on large corpora. International Journal of Corpus Linguistics 19(1). 1–28. https://doi.org/10.1075/ijcl.19.1.01bre.Suche in Google Scholar
Carroll, John B. 1970. An alternative to Juilland’s usage coefficient for lexical frequencies and a proposal for a standard frequency index. Computer Studies in the Humanities and Verbal Behaviour 3(2). 61–65.10.1002/j.2333-8504.1970.tb00778.xSuche in Google Scholar
Church, Kenneth W. & William A. Gale. 1995. Poisson mixtures. Natural Language Engineering 1(2). 163–190. https://doi.org/10.1017/s1351324900000139.Suche in Google Scholar
Davies, Mark. 2008. The corpus of contemporary American English. Available at: www.english-corpora.org/coca.Suche in Google Scholar
Dunning, Ted. 1993. Accurate methods for the statistics of surprise and coincidence. Computational Linguistics 19(1). 61–74.Suche in Google Scholar
Egbert, Jesse, Brent Burch & Douglas Biber. 2020a. Lexical dispersion and corpus design. International Journal of Corpus Linguistics 25(1). 89–115. https://doi.org/10.1075/ijcl.18010.egb.Suche in Google Scholar
Egbert, Jesse & Douglas Biber. 2019. Incorporating text dispersion into keyword analysis. Corpora 14(1). 77–104. https://doi.org/10.3366/cor.2019.0162.Suche in Google Scholar
Egbert, Jesse, Tove Larsson & Douglas Biber. 2020b. Doing linguistics with a corpus: Methodological considerations for the everyday user. Cambridge: Cambridge University Press.10.1017/9781108888790Suche in Google Scholar
Evert, Stefan. 2006. How random is a corpus? The library metaphor. Zeitschrift für Anglistik und Amerikanistik 54(2). 177–190. https://doi.org/10.1515/zaa-2006-0208.Suche in Google Scholar
Gabrielatos, Costas. 2018. Keyness analysis: Nature, metrics and techniques. In Charlotte Taylor & Anna Marchi (eds.), Corpus approaches to discourse: A critical review, 225–258. New York: Routledge.10.4324/9781315179346-11Suche in Google Scholar
Gabrielatos, Costas & Anna Marchi. 2011. Keyness: Matching metrics to definitions. http://eprints.lancs.ac.uk/51449 (accessed 29 March 2023).Suche in Google Scholar
Gries, Stefan Th. 2008. Dispersions and adjusted frequencies in corpora. International Journal of Corpus Linguistics 13(4). 403–437. https://doi.org/10.1075/ijcl.13.4.02gri.Suche in Google Scholar
Gries, Stefan Th. 2020. Analyzing dispersion. In Magali Paquot & Stefan Th. Gries (eds.), A practical handbook of corpus linguistics, 99–118. New York: Springer.10.1007/978-3-030-46216-1_5Suche in Google Scholar
Gries, Stefan Th. 2021. A new approach to (key) keywords analysis: Using frequency, and now also dispersion. Research in Corpus Linguistics 9(2). 1–33. https://doi.org/10.32714/ricl.09.02.02.Suche in Google Scholar
Grissom, Robert J. & John J. Kim. 2012. Effect sizes for research: Univariate and multivariate applications. New York: Routledge.10.4324/9780203803233Suche in Google Scholar
Hardie, Andrew. 2014. Log ratio – An informal introduction. http://cass.lancs.ac.uk/?p=1133 (accessed 29 March 2023).Suche in Google Scholar
Hofland, Knut & Stig Johansson. 1982. Word frequencies in British and American English. London: Longman.Suche in Google Scholar
Juilland, Alphonse G., Dorothy R. Brodin & Catherine Davidovitch. 1970. Frequency dictionary of French words. The Hague: Mouton de Gruyter.Suche in Google Scholar
Kilgarriff, Adam. 1996. Which words are particularly characteristic of a text? A survey of statistical approaches. In Lindsay J. Evett & Tony G. Rose (eds.), Language engineering for document analysis and recognition, 33–40. Nottingham: Nottingham Trent University.Suche in Google Scholar
Kilgarriff, Adam. 2001. Comparing corpora. International Journal of Corpus Linguistics 6(1). 97–133. https://doi.org/10.1075/ijcl.6.1.05kil.Suche in Google Scholar
Kilgarriff, Adam. 2005. Language is never, ever, ever, random. Corpus Linguistics and Linguistic Theory 1(2). 263–276. https://doi.org/10.1515/cllt.2005.1.2.263.Suche in Google Scholar
Kilgarriff, Adam. 2009. Simple maths for keywords. In Michaela Mahlberg, Victorina González-Díaz & Catherine Smith (eds.), Proceedings of the corpus linguistics conference, CL2009. Liverpool: University of Liverpool. http://ucrel.lancs.ac.uk/publications/CL2009/171_FullPaper.doc (accessed 29 March 2023).Suche in Google Scholar
Lijffijt, Jefrey, Terttu Nevalainen, Tanja Säily, Panagiotis Papapetrou, Kai Puolamäki & Heikki Mannila. 2014. Significance testing of word frequencies in corpora. Digital Scholarship in the Humanities 31(2). 374–397. https://doi.org/10.1093/llc/fqu064.Suche in Google Scholar
McEnery, Tony & Andrew Hardie. 2012. Corpus linguistics: Method, theory and practice. Cambridge: Cambridge University Press.10.1017/CBO9780511981395Suche in Google Scholar
Oakes, Michael P. & Malcolm Farrow. 2007. Use of the chi-squared test to examine vocabulary differences in English-language corpora representing seven different countries. Literary and Linguistic Computing 22(1). 85–100. https://doi.org/10.1093/llc/fql044.Suche in Google Scholar
Paquot, Magali. 2010. Academic vocabulary in learner writing. London: Continuum.Suche in Google Scholar
Paquot, Magali & Yves Bestgen. 2009. Distinctive words in academic writing: A comparison of three statistical tests for keyword extraction. In Andreas H. Jucker, Daniel Schreier & Marianne Hundt (eds.), Corpora: Pragmatics and discourse, 247–269. Amsterdam: Rodopi.10.1163/9789042029101_014Suche in Google Scholar
Pojanapunya, Punjaporn & Richard Watson Todd. 2018. Log-likelihood and odds ratio: Keyness statistics for different purposes of keyword analysis. Corpus Linguistics and Linguistic Theory 14(1). 133–167. https://doi.org/10.1515/cllt-2015-0030.Suche in Google Scholar
Rayson, Paul. 2003. Matrix: A statistical method and software tool for linguistic analysis through corpus comparison. Lancaster: Lancaster University dissertation.Suche in Google Scholar
Rayson, Paul, Damon Berridge & Brian Francis. 2004. Extending the Cochran rule for the comparison of word frequencies between corpora. In Gérard Purnelle, Cédrick Fairon & Anne Dister (eds.), Le poids des mots: Proceedings of the 7th International conference on statistical analysis of textual data, 2, 926–936. Louvain-la-Neuve: Presses Universitaires de Louvain.Suche in Google Scholar
Rosengren, Inger. 1971. The quantitative concept of language and its relation to the structure of frequency dictionaries. Études de Linguistique Appliquée (Nouvelle Série) 1. 103–127.Suche in Google Scholar
Scott, Mike. 1997. PC analysis of key words – and key key words. System 25(2). 233–245. https://doi.org/10.1016/s0346-251x(97)00011-0.Suche in Google Scholar
Snedecor, George W. & William G. Cochran. 1989. Statistical methods. Ames: Iowa State University Press.Suche in Google Scholar
Sönning, Lukas. 2023. Key verbs in academic writing: Dataset for “Evaluation of keyness metrics: Performance and reliability”. DataverseNO, V1. Available at: https://doi.org/10.18710/EUXSMW.Suche in Google Scholar
Wilcox, Allen R. 1973. Indices of qualitative variation and political measurement. The Western Political Quarterly 26(2). 325–343. https://doi.org/10.1177/106591297302600209.Suche in Google Scholar
Wilson, Andrew. 2013. Embracing Bayes factors for key item analysis in corpus linguistics. In Markus Bieswanger & Amei Koll-Stobbe (eds.), New approaches to the study of linguistic variability, 3–11. Frankfurt: Peter Lang.Suche in Google Scholar
Winter, Bodo & Martine Grice. 2021. Independence and generalizability in linguistics. Linguistics 59(5). 1251–1277. https://doi.org/10.1515/ling-2019-0049.Suche in Google Scholar
Woods, Anthony, Paul Fletcher & Arthur Hughes. 1986. Statistics in language studies. Cambridge: Cambridge University Press.10.1017/CBO9781139165891Suche in Google Scholar
Zhang, Jun & Kai F. Yu. 1998. What’s the relative risk? A method of correcting the odds ratio in cohort studies of common outcomes. Journal of the American Medical Association 280(19). 1690–1691. https://doi.org/10.1001/jama.280.19.1690.Suche in Google Scholar
© 2023 Walter de Gruyter GmbH, Berlin/Boston
Artikel in diesem Heft
- Frontmatter
- Evaluation of keyness metrics: performance and reliability
- Let my speakers talk: metalinguistic activity can indicate semantic change
- The blurring of the boundaries: changes in verb/noun heterosemy in Recent English
- The linguistic organization of grammatical text complexity: comparing the empirical adequacy of theory-based models
- Present perfect and preterit variation in the Spanish of Lima and Mexico city: findings from a corpus analysis
- Lexical borrowing in Korean: a diachronic approach based on a corpus analysis
- Truth be told: a corpus-based study of the cross-linguistic colexification of representational and (inter)subjective meanings
Artikel in diesem Heft
- Frontmatter
- Evaluation of keyness metrics: performance and reliability
- Let my speakers talk: metalinguistic activity can indicate semantic change
- The blurring of the boundaries: changes in verb/noun heterosemy in Recent English
- The linguistic organization of grammatical text complexity: comparing the empirical adequacy of theory-based models
- Present perfect and preterit variation in the Spanish of Lima and Mexico city: findings from a corpus analysis
- Lexical borrowing in Korean: a diachronic approach based on a corpus analysis
- Truth be told: a corpus-based study of the cross-linguistic colexification of representational and (inter)subjective meanings