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Corpus Methods for Semantics: Quantitative studies in polysemy and synonymy
Edited by Dylan Glynn and Justyna A. Robinson
[Human Cognitive Processing 43] 2014
► pp. 307–341

Techniques and tools

Corpus methods and statistics for semantics

| University of Paris VIII

The use of corpora in semantic research is a rapidly developing method. However, the range of quantitative techniques employed in the field can make it difficult for the non-specialist to keep abreast with the methodological development. This chapter serves as an introduction to the use of corpus methods in Cognitive Semantic research and as an overview of the relevant statistical techniques and software needed for performing them. The discussion and description are intended for researches in semantics that are interested in adopting quantitative corpus-driven methods. The discussion argues that there are fundamentally two corpus-driven approaches to meaning, one based on observable formal patterns (collocation analysis) and another based on patterns of annotated usage-features of use (feature analysis). The discussion then introduces and explains each of the statistical techniques currently used in the field. Examples of the use of each technique are listed and a summary of the software packages available in R for performing the techniques is included.

Keywords: collocation analysis, corpus linguistics, semantics, statistics, usage-feature analysis (behavioural profile)
Published online: 6 November 2014
DOI logo
https://doi.org/10.1075/hcp.43.12gly
References
Adler, J
(2010)  R in a nutshell: A desktop quick reference . Sebastopol: O’Reilly Media.Google Scholar
Afifi, A., May S., & Clark, V.A
(2011)  Practical multivariate analysis (5th ed.). London: Chapman & Hall.Google Scholar
Agresti, A
(2007)  An introduction to categorical data analysis (2nd ed.). Hoboken: John Wiley. DOI logoGoogle Scholar
(2010)  Analysis of ordinal categorical data (2nd ed.). Hoboken: John Wiley. DOI logoGoogle Scholar
(2013) [1990, 2002]  Categorical data analysis (3rd ed.). New York: John Wiley.Google Scholar
Arppe, A
(2006) Frequency considerations in morphology: Finnish verbs differ, too. SKY Journal of Linguistics , 19, 175–189.Google Scholar
(2008) Univariate, bivariate and multivariate methods in corpus-based lexicography – A study of synonymy. Unpublished PhD dissertation, University of Helsinki.Google Scholar
Azen, R., & Walker, C
(2011)  Categorical data analysis for the behavioral and social sciences . New York & Hove: Routledge.Google Scholar
Baayen, R.H
(2008)  Analyzing linguistic data: A practical introduction to statistics using R . Cambridge: Cambridge University Press. DOI logoGoogle Scholar
Baguley, T
(2012)  Loglinear models. Online Supplement 5 to Serious stats: A guide to advanced statistics for the behavioral sciences . Basingstoke: Palgrave. Available at: [URL].Google Scholar
Balahur, A., & Montoyo, A
(2012) Semantic approaches to fine and coarse-grained feature-based opinion mining. In H. Horacek, E. Métais, R. Muñoz, & M. Wolska (Eds.), Natural language processing and information systems (pp. 142–153). Berlin: Springer.Google Scholar
Barnabé, A
(2012) Le schème du chemin en grammaire et sémantique anglaises. Unpublished PhD dissertation, Université Bordeaux 3.Google Scholar
Bates, D
(Forthcoming)  lme4: Mixed-effects modeling with R . Heidelberg & New York: Springer. Preprints available at: [URL].Google Scholar
Benzécri, J.-P
(1980)  Pratique de l’analyse des donnees . Paris: Dunod.Google Scholar
(1992)  Correspondence analysis handbook . New York: Dekker.Google Scholar
Berthele, R
(2010) Investigations into the folk’s mental models of linguistic varieties. In D. Geeraerts, G. Kristiansen, & Y. Peirsman (Eds.), Advances in cognitive sociolinguistics (pp. 265–290). Berlin & New York: Mouton de Gruyter.DOI logoGoogle Scholar
Biber, D
(2009) A corpus-driven approach to formulaic language in English: Multi-word patterns in speech and writing. International Journal of Corpus Linguistics , 14, 275–311. DOI logoGoogle Scholar
Biber, D., & Jones, J
(2009) Quantitative methods in Corpus Linguistics. In A. Lüdeling, & M. Kytö (Eds.), Corpus Linguistics: An international handbook . Vol. 2. (pp. 1287–1304). Berlin & New York: Mouton de Gruyter. DOI logoGoogle Scholar
Borg, I., Groenen, & Mair, P
(2013)  Applied multidimensional scaling . Heidleberg & New York: Springer. DOI logoGoogle Scholar
Borg, I., & Groenen, P
(2005)  Modern multidimensional scaling (2nd ed.). Heidelberg & New York: Springer.Google Scholar
Bresnan, J., Cueni, A., Nikitina, T., & Baayen, H
(2007) Predicting the dative. In G. Bouma, I. Krämer, & J. Zwarts (Eds.), Cognitive foundations of interpretation alternation (pp. 69–94). Amsterdam: Royal Netherlands Academy of Arts and Sciences.Google Scholar
Bybee, J., & Eddington, D
(2006) A usage-based approach to Spanish verbs of ‘becoming’. Language , 82, 323–355. DOI logoGoogle Scholar
Cadoret, M., Lê, S., & Pagès, J
(2011) Multidimensional scaling versus multiple correspondence analysis when analyzing categorization data. In B. Fichet, D. Piccolo, R. Verde, & M. Vichi (Eds.), Classification and multivariate analysis for complex data structures (pp. 301–308). Heidleberg & New York: Springer. DOI logoGoogle Scholar
Chaffin, R
(1992) The concept of a semantic relation. In A. Lehrer, & E. Kittay (Eds.), Frames, fields, and contrasts: New essays in semantic and lexical organisation (pp. 253–288). 
London: Lawrence Erlbaum.Google Scholar
Chatterjee, S., & Hadi, A
(2006)  Regression analysis by example . London: John Wiley. DOI logoGoogle Scholar
Chessel, D., & Dufour, A.-B
(2013) Analysis of ecological data: Exploratory and Euclidean methods in environmental sciences. Available at: [URL].
Chessel, D., Dufour A.-B, & Thioulouse, Y
(2004) The ade4 package – I: One-table methods. R News , 4, 5–10.Google Scholar
Christensen, R
(1997)  Log-linear models and logistic regression (2nd ed.). Heidleberg & New York: Springer.Google Scholar
(2012) A tutorial on fitting cumulative link models with the ordinal package. Available at: [URL].
Clancy, S
(2006) The topology of Slavic case: Semantic maps and multidimensional scaling. Glossos , 7, 1–28.Google Scholar
Colleman, T
(2009) The semantic range of the Dutch double object construction. A collostructional perspective. Constructions and Frames , 1, 190–221. DOI logoGoogle Scholar
(2010) Beyond the dative alternation: The semantics of the Dutch aan-Dative. In D. Glynn, & K. Fischer (Eds.), Quantitative Cognitive Semantics: Corpus-driven approaches (pp. 271–304). Berlin & New York: Mouton de Gruyter.DOI logoGoogle Scholar
Cox, T., & Cox, M
(2001)  Multidimensional scaling (2nd ed.). Boca Raton: Chapman & Hall.Google Scholar
Crawley, M
(2005)  Statistics: An introduction using R . Southern Gate & Hoboken: John Wiley. DOI logoGoogle Scholar
(2007)  The R book . Chichester: John Wiley. DOI logoGoogle Scholar
Croft, W., & Poole, K
(2008) Inferring universals from grammatical variation: Multidimensional scaling for typological analysis. Theoretical Linguistics , 34, 1–37. DOI logoGoogle Scholar
Croissant, Y
(2013) Estimation of multinomial logit models in R: The mlogit packages. Available at: [URL].
Daille, B., Dubreil, E. Monceaux, L., & Vernier, M
(2011) Annotating opinion–evaluation of blogs: The Blogoscopy corpus. Language Resources and Evaluation , 45, 409–437. DOI logoGoogle Scholar
Dalgaard, P
(2008)  Introductory statistics with R (2nd ed.). Dordrecht: Springer. DOI logoGoogle Scholar
De Cock, B
(2014a)  A discourse-functional analysis of speech participant profiling in spoken Spanish . Amsterdam & Philadelphia: John Benjamins. DOI logoGoogle Scholar
(2014b) The discursive effects of Spanish impersonals uno and se . In D. Glynn, & M. Sjölin (Eds.), Subjectivity and epistemicity: Corpus, discourse, and literary approaches to stance (pp. 103–120) . Lund: Lund University Press.Google Scholar
De Leeuw, J., & Mair, P
(2009a) Simple and canonical correspondence analysis using the R package anacor. Journal of Statistical Software , 31, 1–18.Google Scholar
(2009b) Multidimensional scaling using majorization: The R package smacof. Journal of Statistical Software , 31, 1–30.Google Scholar
(2013a) anacor: Simple and canonical correspondence analysis. Available at: [URL].
De Leeuw, J., & Mair, M
(2013b) SMACOF for multidimensional scaling. Available at: [URL].
Deignan, A
(2005)  Metaphor and Corpus Linguistics . Amsterdam & Philadelphia: John 
Benjamins. DOI logoGoogle Scholar
Delorge, M
(2009) A diachronic corpus study of the constructional behaviours of reception verbs in Dutch. In B. Lewandowska-Tomaszczyk, & K. Dziwirek (Eds.), Studies in Cognitive Corpus Linguistics (pp. 249–272). Frankfurt/Main: Peter Lang.Google Scholar
Desagulier, G
(In press) Le statut de la fréquence dans les Grammaires de Constructions: ‘simple comme bonjour’? Langages .Google Scholar
(Submitted) Quite new methods for a rather old issue: Exploring and visualizing collocation data from the BNC with correspondence analysis.
Deshors, S
(2011) A multifactorial study of the uses of may and can in French-English interlanguage. Unpublished PhD dissertation, University of Sussex.Google Scholar
(2014) Identifying different types of non-native co-occurrence patterns: A corpus-based approach. In D. Glynn, & M. Sjölin (Eds.), Subjectivity and epistemicity: Corpus, discourse, and literary approaches to stance (pp. 387–412) . Lund: Lund University Press.Google Scholar
Diehl, H
(2014) On modal meaning in the uses of quite, rather, pretty and fairly as degree modifiers in British English. Unpublished PhD dissertation, Lund University.Google Scholar
Dirven, R., Goossens, L., Putseys, Y., & Vorlat, E
(1982)  The scene of linguistic action and its perspectivization by speak, talk, say, and tell . Amsterdam & Philadelphia: John Benjamins. DOI logoGoogle Scholar
Divjak, D
(2006) Ways of intending: A corpus-based Cognitive Linguistic approach to near-synonyms in Russian. In St. Th. Gries, & A. Stefanowitsch (Eds.), Corpora in Cognitive Linguistics: Corpus-based approaches to syntax and lexis (pp. 19–56). Berlin & New York: Mouton de Gruyter.Google Scholar
(2010a)  Structuring the lexicon: A clustered model for near-synonymy . Berlin & New York: Mouton de Gruyter.Google Scholar
(2010b) Corpus-based evidence for an idiosyncratic aspect-modality relation in Russian. In D. Glynn, & K. Fischer (Eds.), Quantitative Cognitive Semantics: Corpus-driven approaches (pp. 305–331). Berlin & New York: Mouton de Gruyter.DOI logoGoogle Scholar
Divjak, D., & Gries, St. Th
(2006) Ways of trying in Russian: Clustering behavioral profiles. Corpus Linguistics and Linguistic Theory , 2, 23–60. DOI logoGoogle Scholar
(2009) Corpus-based Cognitive Semantics: A contrastive study of phrasal verbs in English and Russian. In B. Lewandowska-Tomaszczyk, & K. Dziwirek (Eds.), Studies in Cognitive Corpus Linguistics (pp. 273–296). Frankfurt/Main: Peter Lang.Google Scholar
(Eds.) (2012)  Frequency effects in language learning and processing . Berlin & New York: Mouton de Gruyter. DOI logoGoogle Scholar
Drenan, R
(2009)  Statistics for archaeologists: A common sense approach (2nd ed.). Heidelberg & New York: Springer.DOI logoGoogle Scholar
Dziwirek, K., & Lewandowska-Tomaszczyk, B
(2011)  Complex emotions and grammatical mismatches: A contrastive corpus-based study . Berlin & New York: Mouton de Gruyter.Google Scholar
Edwards, D
(2000)  Introduction to graphical modelling (2nd ed.). Heidelberg: Springer. DOI logoGoogle Scholar
Everitt, B.S
(2005)  An R and S-PLUS companion to multivariate analysis . London: Springer. DOI logoGoogle Scholar
Everitt, B.S., & Hothorn, I
(2010)  A handbook of statistical analyses using R (2nd ed.). Boca Raton: Taylor & Francis. DOI logoGoogle Scholar
(2011)  An introduction to applied multivariate analysis with R . Munich: Springer. DOI logoGoogle Scholar
Everitt, B.S., Landau, S., Leese, M., & Stahl, D
(2011)  Cluster analysis (5th ed.). Chichester: John Wiley. DOI logoGoogle Scholar
Evert, S
(2009) Corpora and collocations. In A. Lüdeling, & M. Kytö (Eds.), Corpus Linguistics: An international handbook (pp. 1212–1249). Berlin & New York: Mouton de Gruyter. DOI logoGoogle Scholar
Faraway, J
(2002) Practical regression and anova using R. Available at: [URL].
(2006)  Extending the linear model with R: Generalized linear, mixed effects and nonparametric regression models . London: Taylor & Francis.Google Scholar
Field, A., Miles, J., & Field, Z
(2012)  Discovering statistics using R . London & Thousand Oaks: Sage.Google Scholar
Fillmore, C., & Atkins, B
(1992) Toward a frame-based lexicon: The semantics of risk and its neighbours. In A. Lehrer, & E. Kittay (Eds.), Frames, fields, and contrasts: New essays in semantic and lexical organisation (pp. 75–102). London: Lawrence Erlbaum.Google Scholar
Firth, J.R
(1957) A synopsis of linguistic theory 1930–1955. In J.R. Firth (Ed.), Studies in linguistic analysis (pp. 1–32). Oxford: Basil Blackwell.Google Scholar
Fischer, K
(2000)  From Cognitive Semantics to Lexical Pragmatics: The functional polysemy of discourse particles . Berlin & New York: Mouton de Gruyter. DOI logoGoogle Scholar
Flores Salgado, E
(2011)  The pragmatics of requests and apologies: Developmental patterns in Mexican students . Amsterdam & Philadelphia: John Benjamins. DOI logoGoogle Scholar
Fontaine, J., Scherer, K., & Soriano, C
(Eds.) (2013)  Components of emotional meaning: A sourcebook . Oxford: Oxford University Press. DOI logoGoogle Scholar
Funke, S., Mair, P., & von Eye, A
(2007) cfa: R package for the analysis of configuration frequencies. Available at: [URL].
Geeraerts, D
(2010) The doctor and the semantician. In D. Glynn, & K. Fischer (Eds.), Quantitative Cognitive Semantics: Corpus-driven approaches (pp. 63–78). Berlin & New York: Mouton de Gruyter.DOI logoGoogle Scholar
(2011) Entrenchment, conventionalization, and empirical method. Presented at the 44th Meeting of the Societas Linguistica Europaea, Logroño.
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., Grondelaers, S., & Speelman, D
(1999)  Convergentie en Divergentie in de Nederlandse Woordenschat . Amsterdam: Meertens Instituut.Google Scholar
Geeraerts, D., Kristiansen, G., & Peirsman, Y
(Eds.) (2010)  Advances in cognitive sociolinguistics . Berlin & New York: Mouton de Gruyter. DOI logoGoogle Scholar
Gelman, A., & Hill, J
(2007)  Data analysis using regression and multilevel/hierarchical models . Cambridge: Cambridge University Press.Google Scholar
Gilquin, G
(2010)  Corpus, cognition and causative constructions . Amsterdam & Philadelphia: John Benjamins. DOI logoGoogle Scholar
Glynn, D
(2007) Mapping meaning: Toward a usage-based methodology in Cognitive Semantics. Unpublished PhD dissertation, University of Leuven.Google Scholar
(2009) Polysemy, syntax, and variation: A usage-based method for Cognitive Semantics. In V. Evans, & S. Pourcel (Eds.), New directions in Cognitive Linguistics (pp. 77–106). Amsterdam & Philadelphia: John Benjamins. DOI logoGoogle Scholar
(2010a) Synonymy, lexical fields, and grammatical constructions: A study in usage-based Cognitive Semantics. In H.-J. Schmid, & S. Handl (Eds.), Cognitive foundations of linguistic usage-patterns: Empirical studies (pp. 89–118). Berlin & New York: Mouton de Gruyter.DOI logoGoogle Scholar
(2010b) Testing the hypothesis: Objectivity and verification in usage-based Cognitive Semantics. In D. Glynn, & K. Fischer (Eds.), Quantitative Cognitive Semantics: Corpus-driven approaches (pp. 239–270). Berlin & New York: Mouton de Gruyter. DOI logoGoogle Scholar
(2014a) The conceptual profile of the lexeme home: A multifactorial diachronic analysis. In J. E. Díaz-Vera (Ed.), Metaphor and metonymy across time and cultures (pp. 265–293). Berlin & New York: Mouton de Gruyter. Google Scholar
(2014b) The social nature of anger: Multivariate corpus evidence for context effects upon conceptual structure. In I. Novakova, P. Blumenthal, & D. Siepmann (Eds.), Emotions in discourse (pp. 69–82). Frankfurt/Main: Peter Lang.Google Scholar
(Forthcoming)  Mapping meaning: Corpus methods for Cognitive Semantics . 
Cambridge: Cambridge University Press.Google Scholar
Glynn, D., & Sjölin, M
(2011) Cognitive Linguistic methods for literature: A usage-based approach to metanarrative and metalepsis. In A. Kwiatkowska (Ed.), Texts and minds: Papers in cognitive poetics and rhetoric (pp. 85–102). Frankfurt/Main: Peter Lang.Google Scholar
Glynn, D., & Krawczak, K
(Forthcoming) Social cognition, Cognitive Grammar and corpora: A multifactorial approach to epistemic modality. Cognitive Linguistics .Google Scholar
Glynn, D., & Fischer, D
(Eds.) (2010)  Quantitative Cognitive Semantics: Corpus-driven approaches . Berlin & New York: Mouton de Gruyter. DOI logoGoogle Scholar
Glynn, D., & Sjölin, M
(Eds.) (2014)  Subjectivity and epistemicity: Corpus, discourse, and literary approaches to stance . Lund: Lund University Press.Google Scholar
Greenacre, M
(2007) [1993]  Correspondence analysis in practice (2nd ed.). London: Chapman & Hall.DOI logoGoogle Scholar
(2010)  Biplots in practice . Bilbao: Fundación BBVA.Google Scholar
Gries, St. Th
(1999) Particle movement: A cognitive and functional approach. Cognitive Linguistics , 10, 105–145. DOI logoGoogle Scholar
(2000) Towards multifactorial analyses of syntactic variation: The case of particle placement. Doctoral dissertation, University of Hamburg.Google Scholar
(2003)  Multifactorial analysis in Corpus Linguistics: A study of particle placement . London: Continuum Press.Google Scholar
(2006) Corpus-based methods and Cognitive Semantics: The many senses 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
(2009a)  Quantitative Corpus Linguistics with R: A practical introduction . London: Routledge. DOI logoGoogle Scholar
(2009b)  Statistics for Linguistics with R: A practical introduction (1st ed.). Berlin & New York: Mouton de Gruyter. DOI logoGoogle Scholar
(2013)  Statistics for linguistics with R: A practical introduction (2nd ed.). Berlin & New York: Mouton de Gruyter. DOI logoGoogle Scholar
Gries, St. Th., & Divjak, D
(2009) Behavioral profiles: A corpus-based approach to cognitive semantic analysis. In V. Evans, & S. Pourcel (Eds.), New directions in Cognitive Linguistics (pp. 57–75). Amsterdam & Philadelphia: John Benjamins. DOI logoGoogle Scholar
Gries, St. Th., & Hilpert, M
(2008) The identification of stages in diachronic data: Variability-based neighbor clustering. Corpora , 3, 59–81. DOI logoGoogle Scholar
Gries, St. Th., & Stefanowitsch, A
(2004a) Extending collostructional analysis: A corpus-based perspective on ‘alternations’. International Journal of Corpus Linguistics , 9, 97–129. DOI logoGoogle Scholar
(2004b) Co-varying collexemes in the into-causative. In M. Achard, & S. Kemmer (Eds.), Language, culture, and mind (pp. 225–36). Stanford: CSLI.Google Scholar
Gries, St. Th., & Divjak, D
(Eds.) (2012)  Frequency effects in language representation . Berlin & New York: Mouton de Gruyter.DOI logoGoogle Scholar
Gries, St. Th., & Stefanowitsch, A
(Eds.) (2006)  Corpora in Cognitive Linguistics: Corpus-based approaches to syntax and lexis . Berlin & New York: Mouton de Gruyter. DOI logoGoogle Scholar
Grondelaers, S
(2000) De distributie van niet-anaforisch er buiten de eerste zinsplaats: Sociolexicologische, functionele en psycholinguïstische aspecten van er’s status als presentatief signaal. Doctoral dissertation, University of Leuven.Google Scholar
Grondelaers S., Geeraerts, D., & Speelman, D
(2007) A case for a cognitive Corpus Linguistics. In M. Gonzalez-Marquez, I. Mittleberg, S. Coulson, & M. Spivey (Eds.), Methods in Cognitive Linguistics (pp. 149–169). Amsterdam & Philadelphia: John Benjamins. DOI logoGoogle Scholar
Grondelaers S., Speelman, D., & Geeraerts, D
(2008) National variation in the use of er “there”: Regional and diachronic constraints on cognitive explanations. In G. Kristiansen, & R. Dirven (Eds.), Cognitive Sociolinguistics: Language variation, cultural models, social systems (pp. 153–204). Berlin & New York: Mouton de Gruyter.Google Scholar
Hadfield, J
(2010) MCMC methods for multi-response generalized linear mixed models: The MCMCglmm R package. Journal of Statistical Software , 33, 1–22.DOI logoGoogle Scholar
Härdle, W., & Simar, L
(2007)  Applied multivariate statistical analysis . Heidelberg & New York: Springer.Google Scholar
Harrell, F
(2001)  Regression modeling strategies: With Applications to linear models, logistic regression, and survival analysis . Heidelberg & New York: Springer. DOI logoGoogle Scholar
(2012) Regression modeling strategies. Unpublished manuscript, available at: [URL].
Hennig, C
(2013) Flexible procedures for clustering. Available at: [URL].
Heylen, K
(2005a) A quantitative corpus study of German word order variation. In St. Kepser, & M. Reis (Eds.), Linguistic evidence: Empirical, theoretical and computational perspectives (pp.241–264). Berlin & New York: Mouton de Gruyter. DOI logoGoogle Scholar
(2005b) Zur Abfolge (pro)nominaler Satzglieder im Deutschen: Eine korpusbasierte Analyse der relativen Abfolge von nominalem Subjekt und pronominalem Objekt im Mittelfeld, 264. Doctoral dissertation, University of Leuven.Google Scholar
Heylen, K., & Ruette, T
(2013) Degrees of semantic control in measuring aggregated lexical distances. In L. Borin, A. Saxena, A., & T. Rama (Eds.), Approaches to measuring linguistic differences (pp. 353–374). Berlin & New York: Mouton de Gruyter.DOI logoGoogle Scholar
Heylen, K., Tummers, J., & Geeraerts, D
(2008) Methodological issues in corpus-based Cognitive Linguistics. In G. Kristiansen, & R. Dirven (Eds.), Cognitive Sociolinguistics: Language variation, cultural models, social systems (pp. 91–128). Berlin & New York: Mouton de Gruyter. DOI logoGoogle Scholar
Hilbe, J
(2009)  Logistic regression models . London: Chapman & Hall.Google Scholar
(2011) [2007]. Negative binomial regression (2nd ed.). Cambridge: Cambridge University Press.DOI logoGoogle Scholar
Hilpert, M
(2008)  Germanic future constructions: A usage-based approach to language change . Amsterdam & Philadelphia: John Benjamins. DOI logoGoogle Scholar
(2009) The German mit-predicative construction. Constructions and Frames , 1, 29–55. DOI logoGoogle Scholar
(2012)  Constructional change in English: Developments in allomorphy, word formation, and syntax . Cambridge: Cambridge University.Google Scholar
Hoffmann, Th
(2011)  Preposition placement in English: A usage-based approach . Cambridge: Cambridge University Press. DOI logoGoogle Scholar
Hosmer, D., & Lemeshow, S
(2013) [1989, 2000]  Applied logistic regression . Hoboken: John Wiley. DOI logoGoogle Scholar
Hox, J
(2010)  Multilevel analysis: Techniques and applications (2nd ed.). Hove & New York: Routledge.Google Scholar
Husson, F. Josse, J., Lê, S., & Mazet, J
(2013) Multivariate exploratory data analysis and data mining with R. Available at: [URL].
Husson, F., Lê, S., & Pagès, J
(2011)  Exploratory multivariate analysis by example using R . 
London: Chapman & Hall.Google Scholar
Izenman, A
(2008)  Modern multivariate statistical techniques: Regression, classification and manifold learning . Heidelberg & New York: Springer. DOI logoGoogle Scholar
Janda, L., & Solovyev, V
(2009) What constructional profiles reveal about synonymy: A case study of the Russian words for sadness and happiness. Cognitive Linguistics , 20, 367–393. DOI logoGoogle Scholar
Johnson, K
(2008)  Quantitative methods in linguistics . Oxford: Blackwell.Google Scholar
Johnson, V., & Albert, J
(1999)  Ordinal data modeling . Heidelberg & New York: Springer.Google Scholar
Kaufman, L., & Rousseeuw, P
(2005) [1990]  Finding groups in data: An introduction to cluster analysis . Hoboken: John Wiley.Google Scholar
Keen, K
(2010)  Graphics for statistics and data analysis with R . Boca Raton: CRC Press.Google Scholar
Klavan, J
(2012) Evidence in linguistics: Corpus-linguistic and experimental methods for studying grammatical synonymy. Doctoral Dissertation, University of Tartu.Google Scholar
Klavan, J, Kesküla, K., & Ojava, L
(2011) Synonymy in grammar: The Estonian adessive case and the adposition peal ‘on’. In S. Kittilä, K. Västi, & J. Ylikoski (Eds.), Studies on case, animacy and semantic roles (pp. 1–19). Amsterdam & Philadelphia: John Benjamins. DOI logoGoogle Scholar
Krawczak, K
(2014a) Shame and its near-synonyms in English: A multivariate corpus-driven approach to social emotions. In I. Novakova, P. Blumenthal, & D. Siepmann (Eds.), Emotions in discourse (pp. 84–94). Frankfurt/Main: Peter Lang.Google Scholar
(2014b) Epistemic stance predicates in English: A quantitative corpus-driven study of subjectivity. In D. Glynn, & M. Sjölin (Eds.), Subjectivity and epistemicity: Corpus, discourse, and literary approaches to stance (pp. 355–386) . Lund: Lund University Press.Google Scholar
(In press) Corpus evidence for the cross-cultural structure of social emotions: Shame, embarrassment, and guilt in English and Polish. Poznań Studies in Contemporary Linguistics .Google Scholar
Krawczak, K., & Glynn, D
(2011) Context and cognition: A corpus-driven approach to parenthetical uses of mental predicates. In K. Kosecki, & J. Badio (Eds.), Cognitive processes in language (pp. 87–99). Frankfurt/Main: Peter Lang.Google Scholar
Krawczak, K., & Kokorniak, I
(2012) Corpus-driven quantitative approach to the construal of Polish ‘think’. Poznań Studies in Contemporary Linguistics , 48, 439–472. DOI logoGoogle Scholar
Krawczak, K., & Glynn, D
(In press) Operationalising construal: Of/about prepositional profiling for cognitive and communicative predicates. In C.M. Bretones Callejas (Ed.), Construals in language and thought: What shapes what? Amsterdam : John Benjamins.Google Scholar
Kroonenberg, P
(2008)  Applied multiway data analysis . New York: John Wiley. DOI logoGoogle Scholar
Lê, S., Josse, J., & Husson, F
(2008) FactoMineR: An R package for multivariate analysis. Journal of Statistical Software , 25, 1–18.DOI logoGoogle Scholar
Le Roux, B., & Rouanet, H
(2004)  Geometric data analysis: From correspondence analysis to structured data analysis . Dordrecht: Kluwer.Google Scholar
(2010)  Multiple correspondence analysis . London & Thousand Oaks: Sage. DOI logoGoogle Scholar
Ledolter, J
(2013)  Data mining and business analytics with R . Hoboken: John Wiley. DOI logoGoogle Scholar
Lesnoff, M., & Lancelot, R
(2013) Analysis of overdispersed data. Available at: [URL].
Levshina, N
(2011) A usage-based study of Dutch causative constructions. Doctoral dissertation, University of Leuven.Google Scholar
Levshina, N., Geeraerts, D., & Speelman, D
(2013a) Towards a 3D-grammar: Interaction of linguistic and extralinguistic factors in the use of Dutch causative constructions. Journal of Pragmatics , 52, 34–48. DOI logoGoogle Scholar
(2013b) Mapping constructional spaces: A contrastive analysis of English and Dutch analytic causatives. Linguistics , 51, 825–854. DOI logoGoogle Scholar
Lewandowska-Tomaszczyk, B., & Dziwirek, K
(Eds.) (2009)  Studies in Cognitive Corpus Linguistics . Frankfurt/Main: Peter Lang.Google Scholar
Liaw, A., & Wiener, M
(2002) Classification and regression by randomForest. R News , 2, 18–22.Google Scholar
Long, J.S., & Freese, J
(2006) [2001]  Regression models for categorical dependent variables using Stata . College Station: Stata Press.Google Scholar
Louwerse, M., & Van Peer, W
(2009) How cognitive is cognitive poetics? The interaction between symbolic and embodied cognition. In G. Brône, & J. Vandaele (Eds.), Cognitive poetics goals, gains and gaps (pp. 423–444). Berlin & New York: Mouton de Gruyter.Google Scholar
Maechler, M
(2013) Cluster analysis extended. Available at: [URL].
Maindonald, J
(2008) Using R for data analysis and graphics: Introduction, code and commentary. Available at: [URL].
Maindonald, J., & Braun, J
(2010) [2003]  Data analysis and graphics using R (3rd ed.). 
Cambridge: Cambridge University Press.Google Scholar
Marden, J
(2011)  Multivariate statistical analysis: Old school. Department of Statistics, University of Illinois at Urbana-Champaign. Available at: [URL].
Martin, A.D., Quinn, K.M., & Park, J.H
(2010) Markov chain Monte Carlo (MCMC) package. Available at: [URL].
Menard, S
(2002)  Applied logistic regression analysis (2nd ed.). London & Thousand Oaks: Sage.DOI logoGoogle Scholar
(2010)  Logistic regression: From introductory to advanced concepts and applications . London & Los Angeles: Sage.DOI logoGoogle Scholar
Morgenstern, A., Blondel, M., Caët, S., & Boutet, D
(2011) Hearing children’s use of pointing gestures: From pre-linguistic buds to the blossoming of communication skills. Presentation at SALC III, Copenhagen.
Murtagh, F
(2005)  Correspondence analysis and data coding with R and Java . London: Chapman & Hall. DOI logoGoogle Scholar
Myers, D
(1994) Testing for prototypicality: The Chinese morpheme gong . Cognitive Linguistics , 5, 261–280. DOI logoGoogle Scholar
Neandić, O., & Greenacre, M
(2007) Correspondence analysis in R, with two- and three-dimensional graphics: The ca Package. Journal of Statistical Software , 20, 1–13.Google Scholar
Newman, J., & Rice, S
(2004) Patterns of usage for English sit, stand, and lie: A cognitively-inspired exploration in corpus linguistics. Cognitive Linguistics , 15, 351–396. DOI logoGoogle Scholar
(2006) Transitivity schemas of English eat and drink in the BNC. In St. Th. Gries, & A. Stefanowitsch (Eds.), Corpora in Cognitive Linguistics: Corpus-based approaches to syntax and lexis . (pp. 225–260). Berlin & New York: Mouton de Gruyter.Google Scholar
Nordmark, H., & Glynn, D
(2013) anxiety between mind and society: A corpus-driven cross-cultural study of conceptual metaphors. Explorations in English Language and Linguistics , 1, 107–130.Google Scholar
O’Connell, A
(2006)  Logis tic regression models for ordinal response variables . London & Thousand Oaks: Sage.DOI logoGoogle Scholar
Oakes, M
(1998)  Statistics for Corpus Linguistics . Edinburgh: Edinburgh University Press.Google Scholar
Orme, J., & Combs-Orme, T
(2009)  Multiple regression with discrete dependent variables . 
Oxford: Oxford University Press. DOI logoGoogle Scholar
Peirsman, Y. Heylen, K., & Geeraerts, D
(2010) Applying word space models to sociolinguistics: Religion names before and after 9/11. In D. Geeraerts, G. Kristiansen, & Y. Peirsman (Eds.), Advances in Cognitive Sociolinguistics (pp. 111–139). Berlin & New York: Mouton de Gruyter. DOI logoGoogle Scholar
Pęzik, P
(2009) Extraction of multiword expressions for corpus-based discourse analysis. In B. Lewandowska-Tomaszczyk, & K. Dziwirek (Eds.), Studies in Cognitive Corpus Linguistics (pp. 249–272). Frankfurt/Main: Peter Lang.Google Scholar
Pichler, H
(2013)  The structure of discourse-pragmatic variation . Amsterdam & Philadelphia: John Benjamins. DOI logoGoogle Scholar
Plevoets, K., Speelman, D., & Geeraerts, D
(2008) The distribution of T/V pronouns in Netherlandic and Belgian Dutch. In K. Schneider, & A. Baron (Eds.), Variational pragmatics: Regional varieties in pluricentric languages (pp. 181–209). Amsterdam & Philadelphia: John Benjamins. DOI logoGoogle Scholar
Pütz, M, Robinson, J.A., & Reif, M
(Eds.) (2012)  Cognitive Sociolinguistics: Social and cultural variation in cognition and language use . (Special edition of Annual Review of Cognitive Linguistics, 10.)Google Scholar
Ravid, D., & Hanauer, D
(1998) A prototype theory of rhyme: Evidence from Hebrew. Cognitive Linguistics , 9, 79–106. DOI logoGoogle Scholar
Read, J., & Carroll, J
(2012) Annotating expressions of Appraisal in English. Language Resources and Evaluation , 46, 421–447. DOI logoGoogle Scholar
Reif, M., Robinson, J.A., & Pütz, M
(Eds.) (2013)  Variation in language and language use: Linguistic, socio-cultural and cognitive perspectives . Frankfurt/Main: Peter Lang.DOI logoGoogle Scholar
Rencher, A
(2002)  Methods of multivariate analysis (2nd ed.). New York: John Wiley. DOI logoGoogle Scholar
Rice, S., Sandra, D., & Vanrespaille, M
(1999) Prepositional semantics and the fragile link between space and yime. In M. Hiraga, C. Sinha, & S. Wilcox (Eds.), Cultural, typology and psycholinguistic issues in Cognitive Linguistics (pp. 107–127). Amsterdam & Philadelphia: John Benjamins. DOI logoGoogle Scholar
Ripley, B
(2013) Support functions and datasets for Venables and Ripley’s MASS. Available at: [URL].
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. Doctoral dissertation, University of Sheffield.Google Scholar
(2012) A sociolinguistic perspective on semantic change. In K. Allan, & J.A. Robinson (Eds.), Current methods in Historical Semantics (pp. 191–231). Berlin & New York: Mouton de Gruyter.Google Scholar
Roever, C., Raabe, N., Luebke, K., Ligges, U., Szepannek, G., & Zentgraf, M
(2013) Classification and visualization. Unpublished manuscript available at: [URL].
Rudzka-Ostyn, B
(1989) Prototypes, schemas, and cross-category correspondences: The case of ask . In D. Geeraerts (Ed.), Prospects and problems of prototype theory (pp. 613–661). Berlin & New York: Mouton de Gruyter.Google Scholar
(1995) Metaphor, schema, invariance: The case of verbs of answering. In L. Goossens, P. Pauwels, B. Rudzka-Ostyn, A.-M. Simon-Vandenbergen, & J. Vanparys (Eds.), By word of mouth: Metaphor, metonymy, and linguistic action from a cognitive perspective (pp. 205–244). Amsterdam & Philadelphia: John Benjamins. DOI logoGoogle Scholar
Ruette, T., Ehret, K., & Szmrecsanyi, B
(In press)  Frequency effects in lexical sociolectometry are insubstantial . In H. Behrens, & S. Pfänder (Eds.), Again on frequency effects in language . Berlin & New York: Mouton de Gruyter.DOI logoGoogle Scholar
Ruette, T., Geeraerts, D., Peirsman, Y., & Speelman, D
(Forthcoming) Semantic weighting mechanisms in scalable lexical sociolectometry. In B. Szmrecsanyi, & B. Waelchli (Eds.), Aggregating dialectology and typology: Linguistic variation in text and speech, within and across languages . Berlin & New York: Mouton de Gruyter.DOI logoGoogle Scholar
Sagi, E., Kaufmann, S., & Clark, B
(2011) Tracing semantic change with latent semantic analysis. In K. Allan, & J. Robinson (Eds.), Current methods in Historical Semantics (pp. 161–183). Berlin & New York: Mouton de Gruyter.DOI logoGoogle Scholar
Sandra, D., & Rice, S
(1995) Network analyses of prepositional meaning: Mirroring whose mind – the linguist’s or the language user’s? Cognitive Linguistics , 6, 89–130. DOI logoGoogle Scholar
Scheibman, J
(2002)  Point of view and grammar: Structural patterns of subjectivity in American English conversation . Amsterdam & Philadelphia: John Benjamins. DOI logoGoogle Scholar
Scherer, K
(2005) What are emotions? And how can they be measured? Social Science Information , 44, 693–727. DOI logoGoogle Scholar
Schmid, H.-J
(1993)  Cottage and co., idea, start vs. begin: Die kategorisierung als grundprinzip einer differenzierten bedeutungsbeschreibung . Tübingen: Max Niemeyer. DOI logoGoogle Scholar
(2000)  English abstract nouns as conceptual shells: From corpus to cognition . 
Berlin & New York: Mouton de Gruyter. DOI logoGoogle Scholar
Schmidtke-Bode, K
(2009)  Going-to-V and gonna-V in child language: A quantitative approach to constructional development. Cognitive Linguistics , 20, 509–553. DOI logoGoogle Scholar
Schönbrodt, F., Collins, L., & Stemmler, M
(2013) cfa2: Configuration frequency analysis with a design matrix. Available at: [URL].
Schulze, R
(1991) Getting round to (a)round: Towards the description and analysis of a ‘spatial’ predicate. In G. Rauh (Ed.), Approaches to prepositions (pp. 253–74).Tubingen: Günter Narr.Google Scholar
Sheather, S
(2009)  A modern approach to regression with R . New York: Springer. DOI logoGoogle Scholar
Smith, R
(2011)  Multilevel modeling of social problems: A causal perspective . Heidelberg: Springer. DOI logoGoogle Scholar
Speelman, D., & Geeraerts, D
(2010) Causes for causatives: The case of Dutch ‘doen’ and ‘laten’. In T. Sanders, & E. Sweetser (Eds.), Causal categories in discourse and cognition (pp. 173–204). Berlin & New York: Mouton de Gruyter.Google Scholar
Stefanowitsch, A
(2010) Empirical Cognitive Semantics: Some thoughts. In D. Glynn, & K. Fischer (Eds.), Quantitative Cognitive Semantics: Corpus-driven approaches (pp. 355–380). Berlin & New York: Mouton de Gruyter.DOI logoGoogle Scholar
Stefanowitsch, A., & St. Th. Gries
(2003) Collostructions: Investigating the interaction of words and constructions. International Journal of Corpus Linguistics , 8, 209–243. DOI logoGoogle Scholar
(2005) Covarying collexemes. Corpus Linguistics and Linguistic Theory , 1, 1–43. DOI logoGoogle Scholar
(2008) Register and constructional meaning: A collostructional case study. In G. Kristiansen, & R. Dirven (Eds.), Cognitive Sociolinguistics: Language variation, cultural models, social systems (pp. 129–152). Berlin & New York: Mouton de Gruyter. DOI logoGoogle Scholar
Stefanowitsch, A., & Gries, St. Th
(Eds.) (2006)  Corpus-based approaches to metaphor and metonymy . Berlin & New York: Mouton de Gruyter. DOI logoGoogle Scholar
Stevens, J
2001  Applied multivariate statistics for the social sciences (4th ed.). Mahwah: Lawrence Erlbaum.Google Scholar
Strobl, C., Hothorn, T., & Zeileis, A
(2009a) Party on! A new, conditional variable importance measure for random forests available in the party package. The R Journal , 1, 14–17.Google Scholar
Strobl, C., Malley, J., & Gerhard T
(2009b) An introduction to recursive partitioning: Rationale, application, and characteristics of classification and regression trees, bagging, and random forests. Psychological Methods , 14, 323–348. DOI logoGoogle Scholar
Suzuki, R
(2013) Hierarchical clustering with p-values via multiscale bootstrap resampling. Available at: [URL].
Suzuki, R., & Hidetoshi, S
(2006) Pvclust: an R package for assessing the uncertainty in hierarchical clustering. Bioinformatics , 22, 1540–1542. DOI logoGoogle Scholar
Szelid, V, & Geeraerts, D
(2008) Usage-based dialectology: Emotion concepts in the Southern Csango dialect. Annual Review of Cognitive Linguistics , 6, 23–49. DOI logoGoogle Scholar
Szmrecsanyi, B
(2003)  Be going to versus will/shall: Does syntax matter? Journal of English Linguistics , 31, 295–323. DOI logoGoogle Scholar
(2006)  Morphosyntactic persistence in spoken English: A corpus study at the intersection of Variationist Sociolinguistics, Psycholinguistics, and Discourse Analysis . Berlin & New York: Mouton de Gruyter. DOI logoGoogle Scholar
(2010) The English genitive alternation in a cognitive sociolinguistic perspective. In D. Geeraerts, G. Kristiansen, & Y. Peirsman (Eds.), Advances in Cognitive Sociolinguistics (pp. 141–166). Berlin & New York: Mouton de Gruyter.DOI logoGoogle Scholar
(2013)  Grammatical variation in British English dialects . Cambridge: Cambridge University Press.Google Scholar
Tabachnick, B., & Fidell, L
(2007)  Using multivariate statistics (5th ed.). London: Pearson.Google Scholar
Taboada, M., & Carretero, M
(2012) Contrastive analyses of evaluation in text: Key issues in the design of an annotation system for attitude applicable to consumer reviews in English and Spanish. Linguistics and the Human Sciences , 6, 275–295.DOI logoGoogle Scholar
Tarling, R
(2009)  Statistical modelling for social researchers: Principles and practice . London & New York: Routledge.Google Scholar
Therneau, T., Atkinson, EFoundation, M.
& (2013) An introduction to recursive partitioning using the RPART routines. Available at: [URL].
Thompson, L
(2009). S-PLUS (and R) manual to accompany Agresti’s categorical data analysis (2002) . Available at: [URL].Google Scholar
Tummers, J., Heylen, K., & Geeraerts, D
(2005) Usage-based approaches in Cognitive Linguistics: A technical state of the art. Corpus Linguistics and Linguistic Theory , 1, 225–261. DOI logoGoogle Scholar
Valenzuela Manzanares, J., & Rojo López, A.M
(2008) What can language learners tell us about constructions? In S. De Knop, & T. De Rycker (Eds.), Cognitive approaches to pedagogical grammar? A volume in honour of René Dirven (pp. 197–230). Berlin & New York: Mouton de Gruyter.Google Scholar
Van Bogaert, J
(2010) A constructional taxonomy of I think and related expressions: Accounting for the variability of complement-taking mental predicates. English Language and Linguistics , 14, 399–428. DOI logoGoogle Scholar
Venables, W., & Ripley, B
(2002)  Modern applied statistics with S (4th ed.). Heidelberg: Springer. DOI logoGoogle Scholar
Verdonik, D., Rojc, M., & Stabej, M
(2007) Annotating discourse markers in spontaneous speech corpora on an example for the Slovenian language. Language Resources and Evaluation , 41, 147–180. DOI logoGoogle Scholar
von Eye, A
(2002)  Configural frequency analysis: Methods, models, and applications . Mahwah: Erlbaum.Google Scholar
von Eye, A., & Mair, P
(2008) A functional approach to configural frequency analysis. Austrian Journal of Statistics , 37, 161–173.Google Scholar
von Eye, A, Mair, P., & Mun, E.-Y
(2010)  Advances in configural frequency analysis . London: Guilford Press.Google Scholar
von Eye, A, & Mun, E.-Y
(2013)  Log-linear modeling: Concepts, interpretation, and application . Hoboken: John Wiley.Google Scholar
Wiebe, J., Wilson, T., & Cardie, C
(2005) Annotating expressions of opinions and emotions in language. Language Resources and Evaluation , 39, 165–210. DOI logoGoogle Scholar
Wiechmann, D
(2008) On the computation of collostruction strength: Testing measures of association as expressions of lexical bias. Corpus Linguistics and Linguistic Theory , 4, 253–290. DOI logoGoogle Scholar
Wong, M
(2009)  Gei constructions in Mandarin Chinese and bei constructions in Cantonese: A corpus-driven contrastive study. International Journal of Corpus Linguistics , 14, 60–80. DOI logoGoogle Scholar
Wulff, S
(2003) A multifactorial corpus analysis of adjective order in English. International Journal of Corpus Linguistics , 8, 245–82. DOI logoGoogle Scholar
(2006)  Go-V vs. go-and-V in English: A case of constructional synonymy? In St. Th. Gries, & A. Stefanowitsch (Eds.), Corpora in Cognitive Linguistics: Corpus-based approaches to syntax and lexis (pp. 101–126). Berlin & New York: Mouton de Gruyter.Google Scholar
(2009)  Rethinking idiomaticity: A usage-based approach . London: Continuum.Google Scholar
(2010) Marrying cognitive-linguistic theory and corpus-based methods: On the compositionality of English V NP-idioms. In D. Glynn, & K. Fischer (Eds.), Quantitative Cognitive Semantics: Corpus-driven approaches (pp. 223–238). Berlin & New York: Mouton de Gruyter.DOI logoGoogle Scholar
Wulff, S., Stefanowitsch, A., & Gries, St. Th
(2007) Brutal Brits and persuasive Americans: Variety-specific meaning construction in the into-causative. In G. Radden, Köpcke, K.-M., Berg, Th., & Siemund, P. (Eds.), Aspects of meaning construction (pp. 265–281). Amsterdam & Philadelphia: John Benjamins. DOI logoGoogle Scholar
Zeschel, A
(2010) Exemplars and analogy: Semantic extension in constructional networks. In D. Glynn, & K. Fischer (Eds.), Quantitative Cognitive Semantics: Corpus-driven approaches (pp. 201–221). Berlin & New York: Mouton de Gruyter.DOI logoGoogle Scholar
Zhao, Y
(2013) R and data mining: Examples and case studies. Unpublished manuscript. Available at: [URL].
Zlatev, J., & Andrén, M
(2009) Stages and transitions in children’s semiotic development. In J. Zlatev, M. Andrén, C. Lundmark, & M. Johansson Falck (Eds.), Studies in language and cognition (pp. 380–401). Newcastle: Cambridge Scholars.Google Scholar
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