LEADER 05852nam 2200769 450 001 9910459981503321 005 20200903223051.0 010 $a90-272-7033-3 035 $a(CKB)3710000000270460 035 $a(EBL)1824201 035 $a(SSID)ssj0001367725 035 $a(PQKBManifestationID)11784422 035 $a(PQKBTitleCode)TC0001367725 035 $a(PQKBWorkID)11445281 035 $a(PQKB)11153638 035 $a(MiAaPQ)EBC1824201 035 $a(PPN)185098398 035 $a(Au-PeEL)EBL1824201 035 $a(CaPaEBR)ebr10960631 035 $a(CaONFJC)MIL663015 035 $a(OCoLC)894170695 035 $a(EXLCZ)993710000000270460 100 $a20141107h20142014 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aCorpus methods for semantics $equantitative studies in polysemy and synonymy /$fedited by Dylan Glynn, Justyna A. Robinson ; contributors, Timothy Colleman [and twenty-two others] 210 1$aAmsterdam, Netherlands ;$aPhiladelphia, Pennsylvania :$cJohn Benjamins Publishing Company,$d2014. 210 4$dİ2014 215 $a1 online resource (553 p.) 225 1 $aHuman Cognitive Processing,$x1387-6724 ;$vVolume 43 300 $aDescription based upon print version of record. 311 $a1-322-31733-X 311 $a90-272-2397-1 320 $aIncludes bibliographical references at the end of each chapters and indexes. 327 $aCorpus Methods for Semantics; Editorial page; Title page; LCC data; Table of contents; Contributors; Outline; 1. Aim of the volume; 2. Structure and summary; References; Section 1. Polysemy and synonymy; Polysemy and synonymy: Cognitive theory and corpus method; 1. Introduction: Theory and method; 2. Polysemy and synonymy: Definition, object and operationalisation; 3. Complexity and sampling: The need for quantification; 4. Modelling meaning. Multidimensional patterns and prototype effects; References; Competing 'transfer' constructions in Dutch: The case of ont-verbs; 1. Introduction 327 $a2. Introducing the Dutch ont-verbs3. Methodology of the case study; 4. The results of the present-day investigation; 5. A diachronic perspective; 6. Conclusion; References; Appendix; Rethinking constructional polysemy: The case of the English conative construction; 1. Introduction; 2. The conative construction; 3. A collexeme analysis of the conative construction; 4. A collexeme analysis of verb-class-specific constructions; 5. Conclusion; References; Quantifying polysemy in cognitive sociolinguistics; 1. Polysemy; 2. Scope of the study; 3. Data and method 327 $a4. Hierarchical agglomerative clustering5. Hierarchical agglomerative cluster analysis of collected data; 6. Logistic regression; 7. Decision tree analysis; 8. Summary and discussion of results; References; The many uses of run: Corpus methods and Socio-Cognitive Semantics; 1. Introduction; 2. Usage-based Cognitive Semantics; 3. Case study: run in America and Britain in diaries and conversation; 4. Summary; References; Visualizing distances in a set of near-synonyms: Rather, quite, fairly, and pretty; 1. Introduction; 2. Previous research; 3. Method; 4. Results; 5. Discussion and conclusion 327 $aReferencesA case for the multifactorial assessment of learner language: The uses of may and can in French-English interlanguage; 1. Introduction and overview; 2. Setting the stage; 3. Data and methods; 4. Results and discussion; 5. Concluding remarks; References; Dutch causative constructions: Quantification of meaning and meaning of quantification; 1. Introduction; 2. Dutch causative constructions; 3. Data and variables; 4. Statistical analysis; 5. Linguistic interpretation of the statistical models; 6. Conclusion; References 327 $aThe semasiological structure of Polish mys?lec? 'to think': A study in verb-prefix semantics1. Introduction; 2. Introspective conceptual analysis of the prefixed forms of mys?lec? 'to think' in Polish; 3. The corpus; 4. Feature annotation; 5. Multivariate analysis of the results of feature annotation; 6. Conclusion; References; A multifactorial corpus analysis of grammatical synonymy: The Estonian adessive and adposition peal ; 1. Introduction; 2. The Estonian adessive case and the adposition peal 'on'; 3. The data sample; 4. Corpus-linguistic operationalizations and monofactorial results 327 $a5. Multifactorial results. Logistic regression analysis 330 $aThis text offers an introduction to binary logistic regression, a confirmatory technique for statistically modelling the effect of one or several predictors on a binary response variable. It is explained why logistic regression is exceptionally well suited for the comparison of near-synonyms in corpus data; the technique allows the researcher to identify the different factors that have an impact on the choice between near synonyms, and to tease apart their respective effects. Moreover, the technique is well suited to deal with the type of unbalanced data sets that are typical of Corpus Linguis 410 0$aHuman cognitive processing ;$vVolume 43. 606 $aSemantics 606 $aCognitive grammar 606 $aComputational linguistics 606 $aPolysemy 606 $aCorpora (Linguistics) 608 $aElectronic books. 615 0$aSemantics. 615 0$aCognitive grammar. 615 0$aComputational linguistics. 615 0$aPolysemy. 615 0$aCorpora (Linguistics) 676 $a401/.43 702 $aGlynn$b Dylan 702 $aRobinson$b Justyna A. 702 $aColleman$b Timothy 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910459981503321 996 $aCorpus methods for semantics$92259705 997 $aUNINA