Correspondence analysis
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Dylan Glynn
Abstract
Correspondence analysis is an exploratory technique for complex categorical data, typical of corpus-driven research. It identifies patterns of association and disassociation in those data. For instance, it can map the correlations between different uses of a linguistic form and its various social and/or morpho-syntactic contexts. The technique presents its results in the form of a two-dimensional plot, which visualises these relationships in an intuitive manner. These plots offer rich representations of the relations between different facets of complex data. Using R, this chapter explains how the technique works and offers a step-by-step explanation of its application and the interpretation of its results. The technique is also compared to the better-known and comparable cluster analysis.
Abstract
Correspondence analysis is an exploratory technique for complex categorical data, typical of corpus-driven research. It identifies patterns of association and disassociation in those data. For instance, it can map the correlations between different uses of a linguistic form and its various social and/or morpho-syntactic contexts. The technique presents its results in the form of a two-dimensional plot, which visualises these relationships in an intuitive manner. These plots offer rich representations of the relations between different facets of complex data. Using R, this chapter explains how the technique works and offers a step-by-step explanation of its application and the interpretation of its results. The technique is also compared to the better-known and comparable cluster analysis.
Kapitel in diesem Buch
- Prelim pages i
- Table of contents v
- Contributors vii
- Outline 1
-
Section 1. Polysemy and synonymy
- Polysemy and synonymy 7
- Competing ‘transfer’ constructions in Dutch 39
- Rethinking constructional polysemy 61
- Quantifying polysemy in Cognitive Sociolinguistics 87
- The many uses of run 117
- Visualizing distances in a set of near-synonyms 145
- A case for the multifactorial assessment of learner language 179
- Dutch causative constructions 205
- The semasiological structure of Polish myśleć ‘to think’ 223
- A multifactorial corpus analysis of grammatical synonymy 253
- A diachronic corpus-based multivariate analysis of “I think that” vs. “I think zero” 279
-
Section 2. Statistical techniques
- Techniques and tools 307
- Statistics in R 343
- Frequency tables 365
- Collostructional analysis 391
- Cluster analysis 405
- Correspondence analysis 443
- Logistic regression 487
- Name index 535
- Subject index 541
Kapitel in diesem Buch
- Prelim pages i
- Table of contents v
- Contributors vii
- Outline 1
-
Section 1. Polysemy and synonymy
- Polysemy and synonymy 7
- Competing ‘transfer’ constructions in Dutch 39
- Rethinking constructional polysemy 61
- Quantifying polysemy in Cognitive Sociolinguistics 87
- The many uses of run 117
- Visualizing distances in a set of near-synonyms 145
- A case for the multifactorial assessment of learner language 179
- Dutch causative constructions 205
- The semasiological structure of Polish myśleć ‘to think’ 223
- A multifactorial corpus analysis of grammatical synonymy 253
- A diachronic corpus-based multivariate analysis of “I think that” vs. “I think zero” 279
-
Section 2. Statistical techniques
- Techniques and tools 307
- Statistics in R 343
- Frequency tables 365
- Collostructional analysis 391
- Cluster analysis 405
- Correspondence analysis 443
- Logistic regression 487
- Name index 535
- Subject index 541
