Cover not available
Part of
Corpus Methods for Semantics: Quantitative studies in polysemy and synonymy
Edited by Dylan Glynn and Justyna A. Robinson
[Human Cognitive Processing 43] 2014
► pp. 87–115

Quantifying polysemy in Cognitive Sociolinguistics

ORCID logo | University of Sussex

This chapter uses various statistical techniques to explore the extralinguistic grounding of individual conceptualisations of polysemous adjectives in English, such as awesome, gay, wicked. It considers the extent to which individual conceptualisations are non-random and can be related to the socio-demographic characteristics of the speaker. The experimental survey data collected from 72 speakers is analysed via hierarchical agglomerative clustering, decision tree analysis, and logistic regression analysis. The results reveal that not only individual adjectives, as indicated in Robinson (2010a), but whole groups of polysemous adjectives currently undergoing semantic change form usage patterns that can be explained by a very similar sociolinguistic distribution. This study demonstrates that employing a socio-cognitive perspective when researching polysemy is hugely advantageous.

Keywords: adjectives, decision tree analyses, hierarchical agglomerative clustering, logistic regression, semantic change, semantic variation
Published online: 6 November 2014
DOI logo
https://doi.org/10.1075/hcp.43.04rob
References
Aldenderfer, M.S., & Blashfield, R
(1984)  Cluster analysis . Sage Publications: Newbury Park.Google Scholar
Allan, K. & Robinson, J.A
(Eds.) (2012)  Current methods in historical semantics . Berlin & Boston: Mouton de Gruyter.Google Scholar
Barrio, G., De La Fuente, L., Toro, C., Vicente, T.M., Vallejo, F., & Silva, T
(2006) Prevalence of HIV infection among young adult injecting and non-injecting heroin users in Spain in the era of harm reduction programmes: Gender differences and other related factors. Epidemiology and Infection , 135(4), 592–603. DOI logoGoogle Scholar
Beitel, D.A., Gibbs, R., & Sanders, P
(2001) The embodied approach to the polysemy of the spatial preposition on . In H. Cuyckens, & B. Zawada (Eds.), Polysemy in Cognitive Linguistics (pp. 241–260). Amsterdam: Benjamins. DOI logoGoogle Scholar
Benki, J.R
(1998) Evidence for phonological categories from speech perception. Unpublished PhD dissertation, University of Massachusetts.Google Scholar
Beretta, A., Fiorentino, R., & Poeppel, D
(2005) The effects of homonymy and polysemy on lexical access: An MEG study. Cognitive Brain Research , 24(1), 57–65. DOI logoGoogle Scholar
Blank, A
(2003) Polysemy in the lexicon and in discourse. In B. Nerlich, Z. Todd, 
V. Herman, & D.D. Clarke (Eds.), Polysemy: Flexible patterns of meaning in mind and language (pp. 267–293). Berlin & New York: Mouton de Gruyter. DOI logoGoogle Scholar
Boscarino, J.A., Galea, S., Ahern, J., Resnick, H., & Vlahov, D
(2003) Psychiatric medication use among Manhattan residents following the World Trade Center disaster. Journal of Traumatic Stress , 16(3), 301–306. DOI logoGoogle Scholar
Brace, N., Kemp, R., & Snelgar, R
(2006)  SPSS for psychologists , 3rd edition. New York: Palgrave Macmillan.Google Scholar
Breckenridge, J.N
(2000) Validating cluster analysis: Consistent replication and symmetry. Multivariate Behavioural Research , 35(2), 261–286. DOI logoGoogle Scholar
Bresnan, J., Cueni, A., Nikitina, T., & Baayen, R.H
(2007) Predicting the dative alternation. In G. Boume, I. Kraemer, & J. Zwarts (Eds.), Cognitive foundations of interpretation (pp. 69–94). Amsterdam: Royal Netherlands Academy of Science.Google Scholar
The British National Corpus
, Version 3 (BNC XML Edition). Accessed via [URL] [March 2008].
Brugman, C
(1981) Story of over. MA thesis, University of California, Berkley.Google Scholar
Bucholtz, M
(2011)  White kids: Language, race and styles of youth identity . Cambridge: Cambridge University Press.Google Scholar
Chambers, J.K., Trudgill, P., & Schilling-Estes, N
(2002)  The handbook of language variation and change . Oxford: Blackwell.Google Scholar
Chaturvedi, A., & Green, P.E
(1995) Software review: SPSS for Windows, CHAID 6.0. Journal of Marketing Research , 32, 245–254. DOI logoGoogle Scholar
Clatworthy, J., Buick, D., Hankins, M., Weinman, J., & Horne, R
(2005) The use and reporting of cluster analysis in health psychology: A review. British Journal of Health Psychology , 10(3), 329–358. DOI logoGoogle Scholar
Coulmas, F
(Ed.) (1997)  The handbook of sociolinguistics . Oxford: Blackwell.Google Scholar
Cuyckens, H., & Zawada, B
(Eds.) (2001)  Polysemy in Cognitive Linguistics . Amsterdam & Philadelphia: John Benjamins. DOI logoGoogle Scholar
Divjak, D., & Gries, St. Th
(2006) Ways of trying in Russian: Clustering behavioral profiles. Corpus Linguistics and Linguistic Theory , 2(1), 23–60. DOI logoGoogle Scholar
Duda, R., Hart, P., & Stork, D
(2001)  Pattern classification . New York: Wiley Interscience.Google Scholar
Dunbar, G
(2001) Towards a cognitive analysis of polysemy, ambiguity, and vagueness. Cognitive Linguistics , 12(1), 1–14. DOI logoGoogle Scholar
Eckert, P
(2000)  Linguistic variation as social practice . Oxford: Blackwell.Google Scholar
Einspruch, E.L
(2005)  An introductory guide to SPSS® for Windows® , 2nd edition. Thousand Oaks, London & New Delhi: Sage Publications.Google Scholar
Everitt, B.S., Landau, S., & Leese, M
(2001)  Cluster analysis . London: Arnold.Google Scholar
Field, A
(2005)  Discovering statistics using SPSS. London: Sage .Google Scholar
Fought, C
(2004)  Sociolinguistic variation: Critical reflections . Oxford: Oxford University Press.Google Scholar
Geeraerts, D
(1989) Prospects and problems of prototype theory. Linguistics , 27(4), 587–612. DOI logoGoogle Scholar
(1993) Vagueness’s puzzles, polysemy’s vagaries. Cognitive Linguistics , 4(3), 223–272. DOI logoGoogle Scholar
(1997)  Diachronic prototype semantics: A contribution to historical-lexicology . Oxford: Clarendon Press.Google Scholar
Geeraerts, D., Grondelaers, S., & Bakema, P
(1994)  The structure of lexical variation. Meaning, naming, and context . Berlin & New York: Mouton de Gruyter. DOI logoGoogle Scholar
Geeraerts, D., & Cuyckens, H
(Eds.) (2007)  Oxford handbook of Cognitive Linguistics . Oxford: Oxford University Press.Google Scholar
Geeraerts, D., Kristiansen, G., & Piersman, Y
(Eds.) (2010)  Advances in Cognitive Sociolinguistics . Berlin & New York: Mouton de Gruyter. DOI logoGoogle Scholar
Gries, St. Th
(2006) Corpus-based methods and Cognitive Semantics: The many meanings of to run . In St. Th. Gries, & A. Stefanowitsch (Eds.), Corpora in Cognitive Linguistics: Corpus-based approaches to syntax and lexis (pp. 57–99). Berlin & New York: Mouton de Gruyter. DOI logoGoogle Scholar
(2007) Cluster analysis: A practical introduction with R (for Windows). Paper presented at Departmental Research Seminar, University of Sheffield.
Gries, St. Th., & Stefanowitsch, A
(2006) Cluster analysis and the identification of collexeme classes. In S. Rice, & J. Newman (Eds.), Empirical and experimental methods in cognitive/functional research . Stanford: CSLI.Google Scholar
Hanks, P
(2000) Do word meanings exist? Computers and the Humanities , 34(1–2), 205–215. DOI logoGoogle Scholar
Heylen, K
(2005) A quantitative corpus study of German word order variation. In S. Kepser, & M. Reis (Eds.), Linguistic evidence: Empirical, theoretical and computational perspectives (pp. 241–264). Berlin: Mouton de Gruyter. DOI logoGoogle Scholar
Hosmer, D.W., & Lemeshow, S
(1989)  Applied logistic regression . New York: Wiley.Google Scholar
Janda, L
(1990) The radial network of a grammatical category – its genesis and dynamic structure. Cognitive Linguistics , 1(3), 269–288. DOI logoGoogle Scholar
Kallel, A
(2007) The loss of negative concord in Standard English: Internal factors. Language Variation and Change , 19(1), 27–49. DOI logoGoogle Scholar
Kilgariff, A
(1997) I don’t believe in word senses. Computers and the Humanities , 31(2), 91–113. DOI logoGoogle Scholar
Klein, D., & Murphy, G.L
(2002) Paper has been my ruin: Conceptual relations of polysemous senses. Journal of Memory and Language , 47(4), 548–570. DOI logoGoogle Scholar
Kleinbaum, D.G
(1994)  Logistic regression: A self-learning text . New York: Springer-Verlag. DOI logoGoogle Scholar
Krishnamurthy, R., & Nicholls, D
(2000) Peeling an onion: A lexicographer’s experience of manual sense-tagging. Computers and the Humanities , 34(1–2), 85–97. DOI logoGoogle Scholar
Kristiansen, G., & Dirven, R
(Eds.) (2008)  Cognitive Sociolinguistics: Language variation, cultural models, social systems . Berlin: Mouton de Gruyter. DOI logoGoogle Scholar
Labov, W
(2001)  Principles of linguistic change: Social factors . Oxford: Blackwell.Google Scholar
Lakoff, G
(1987)  Women, fire, and dangerous things: What categories reveal about the mind . Chicago: Chicago University Press. DOI logoGoogle Scholar
Lehrer, A
(1990) Polysemy, conventionality, and the structure of the lexicon. Cognitive Linguistics , 1(2), 207–246. DOI logoGoogle Scholar
Lewandowska-Tomaszczyk, B
(2007) Polysemy, prototypes and radial categories. In 
D. Geeraerts, & H. Cuyckens (Eds.), Oxford handbook of Cognitive Linguistics (pp. 139–169). Oxford: Oxford University Press.Google Scholar
Magidson, J
(1994) The CHAID approach to segmentation modelling. In R.P. Bagozzi (Ed.), Advanced methods of marketing research (pp. 118–159). Cambridge, MA.: Blackwell.Google Scholar
Milligan, G.W., & Cooper, M.C
(1986) A study of comparability of external criteria for hierarchical cluster analysis. Multivariate Behavioural Research , 21(4), 41–58. DOI logoGoogle Scholar
Milroy, L
(1980)  Language and social networks . Oxford: Blackwell.Google Scholar
(1987)  Observing and analysing natural language: A critical account of sociolinguistic method . Oxford & New York: Blackwell.Google Scholar
Moisl, H.L
(2009) Exploratory multivariate analysis. In A. Lüdeling, & M. Kytö (Eds.), Corpus linguistics: An international handbook (pp. 874–898). Berlin: Mouton de Gruyter. DOI logoGoogle Scholar
Moisl, H.L., & Jones, V
(2005) Cluster analysis of the Newcastle Electronic Corpus of Tyneside English: A comparison of methods. Literary and Linguistic Computing , 20(1), 125–146. DOI logoGoogle Scholar
Mojena, R
(1977) Hierarchical grouping methods and stopping rules: An evaluation. Computer Journal , 20(4), 359–363. DOI logoGoogle Scholar
Moss, M., Wellman, D.A., & Cotsonis, G.A
(2003) An appraisal of multivariable logistic models in the pulmonary and critical care literature. Chest , 123(3), 923–928. DOI logoGoogle Scholar
Nerlich, B., Todd, Z., & Clarke, D.D
(2003) The acquisition of get between four and ten years. In B. Nerlich, Z. Todd, V. Herman, & D. Clarke (Eds.), Polysemy: Flexible patterns of meaning in mind and language (pp. 333–357). Berlin & New York: Mouton de Gruyter. DOI logoGoogle Scholar
Nerlich, B., Todd Z., Herman, V., & Clarke, D.D
(2003)  Polysemy: Flexible patterns of meaning in mind and language . Berlin & New York: Mouton de Gruyter. DOI logoGoogle Scholar
Norušis, M.J
(1999)  SPSS regression models 10.0 . Chicago: SPSS Inc.Google Scholar
(
2000)  Standard Occupational Classification . Volume 2. Coding Index. London: The Stationery Office.Google Scholar
The Oxford English Corpus
. Accessed via [URL] [March 2008].
Oxford English Dictionary Online
. Oxford University Press. Accessed via [URL] [March 2008].
Peng, C.-Y.J., Lee, K.L., & Ingersoll, G.M
(2002) An introduction to logistic regression analysis and reporting. Journal of Educational Research , 96(1), 3–14. DOI logoGoogle Scholar
Pütz, M., Robinson, J.A., & Reif, M
(Eds.) (2012a) Cognitive Sociolinguistics: Variation in cognition and language use. Special issue of Review of Cognitive Linguistics , 10(2). DOI logoGoogle Scholar
Pütz, M, Robinson, J.A., & Reif, M
(2012b) The emergence of Cognitive Sociolinguistics: An introduction. Annual Review of Cognitive Linguistics , 10(2), 241–263. DOI logoGoogle Scholar
Pütz, M., Robinson, J.A., & Reif, M
(Eds.) (2014) Cognitive Sociolinguistics. Social and cultural variation in cognition and language use. Benjamins Current Topics, 59. Amsterdam/Philadelphia: John Benjamins. DOI logoGoogle Scholar
Rakova, M., Pethő, G., & Rákosi, C
(Eds.) (2007)  The cognitive basis of polysemy: New sources of evidence for theories of word meaning . Frankfurt/Main: Peter Lang.Google Scholar
Rao, V.R., & Steckel, J.H
(1995) Selecting, evaluating, and updating prospects in direct mail marketing. Journal of Direct Marketing , 9(20), 20–31. DOI logoGoogle Scholar
Ravin, Y., & Leacock, C
(Eds.) (2000)  Polysemy: Theoretical and computational approaches . Oxford: Oxford University Press.Google Scholar
Reif, M., Robinson, J.A., & Pütz, M
(Eds.) (2013)  Variation in language and language use: Sociolinguistic, socio-cultural and cognitive perspectives . Frankfurt/Main: Peter Lang.Google Scholar
Robinson, J.A
(2010a)  Awesome insights into semantic variation. In D. Geeraerts, 
G. Kristiansen, & Y. Piersman (Eds.), Advances in Cognitive Sociolinguistics (pp. 85–109). Berlin & New York: Mouton de Gruyter.DOI logoGoogle Scholar
(2010b) Semantic variation and change in present-day English. Unpublished PhD dissertation, University of Sheffield. Available via [URL]Google Scholar
(2012a) A sociolinguistic perspective on semantic change. In K. Allan, & J.A. Robinson (Eds.), Current methods in historical semantics (pp. 191–231). Berlin & Boston: Mouton de Gruyter.Google Scholar
(2012b) A gay paper: Why should sociolinguistics bother with semantics? English Today , 28(4), 38–54. DOI logoGoogle Scholar
Saltini, A., Mazzi, M.A., Del Piccolo, L., & Zimmermann, C
(2004) Decisional strategies for the attribution of emotional distress in primary care. Psychological Medicine , 34(4), 729–739. DOI logoGoogle Scholar
Schmid, H.J
(2010) Decision trees. In A. Clark, C. Fox, & S. Lappin (Eds.), The handbook of computational linguistics and natural language processing (pp. 180–196). Oxford: Blackwell. DOI logoGoogle Scholar
SPSS
(2005) Answer tree algorithm summary; SPSS white paper series.
Sweetser, E
(1990)  From etymology to pragmatics: Metaphorical and cultural aspects of semantic structure . Cambridge: Cambridge University Press. DOI logoGoogle Scholar
Tabachnick, B.G., & Fidell, L.S
(2001)  Using multivariate statistics . Boston: Allyn and Bacon.Google Scholar
Tan, P.-N., Steinbach, M., & Kumar, V
(2006)  Introduction to data mining . Boston: Pearson Addison-Wesley.Google Scholar
Taylor, J.R
(1995)  Linguistic categorization: Prototypes in linguistic theory . Oxford: Oxford University Press.Google Scholar
Tummers, J., Speelman, D., & Geeraerts, D
(2004) Quantifying semantic effects: The impact of lexical collocations on the inflectional variation of Dutch attributive adjectives. In 
G. Purnelle, C. Fairon, & A. Dister (Eds.), Le poids des Mots: Actes des 7emes journées internationales d’analyse statistique des données textuelles (pp. 1079–1088). Louvain-la-Neuve: Presses Universitaires de Louvain.Google Scholar
Cited by

Cited by 6 other publications

Dattner, Elitzur
2019. The Hebrew dative: Usage patterns as discourse profile constructions. Linguistics 57:5 ► pp. 1073 ff. DOI logo
Proos, Mariann
2019. Chapter 12. Polysemy of the Estonian perception verb nägema ‘to see’. In Perception Metaphors [Converging Evidence in Language and Communication Research, 19], ► pp. 231 ff. DOI logo
Robinson, Justyna A. & Julie Weeds
2022. Cognitive Sociolinguistic Variation in the Old Bailey Voices Corpus: The Case for a New Concept‐Led Framework. Transactions of the Philological Society 120:3 ► pp. 399 ff. DOI logo
Sandow, Rhys
2024. The Role of Local Identity in the Usage and Recognition of Anglo-Cornish Dialect Lexis. Journal of English Linguistics 52:1 ► pp. 38 ff. DOI logo
Sandow, Rhys J.
2023. Maidin Cornwall. English World-Wide. A Journal of Varieties of English 44:2 ► pp. 157 ff. DOI logo
SANDOW, RHYS J., GEORGE BAILEY & NATALIE BRABER
2024. Language change is wicked: semantic and social meaning of a polysemous adjective. English Language and Linguistics 28:1 ► pp. 135 ff. DOI logo

This list is based on CrossRef data as of 20 april 2024. Please note that it may not be complete. Sources presented here have been supplied by the respective publishers. Any errors therein should be reported to them.