Looking for contextual cues to differentiate modal meanings: a corpus-based study

Lyashevskaya Olga, Ovsjannikova Maria, Nina Szymor, Dagmar Divjak

Research output: Chapter in Book/Report/Conference proceedingChapter


The domain of modality is structurally diverse and may be described in multiple ways. Another way of classification concerns possible functions of modal words, such as possibility, ability, permission, necessity, obligation, or probability. These categories usually come from traditional grammars and textbooks. For each modal word, a sample of 250 independent observations was extracted and annotated. Multiple correspondence analysis (MCA) is a post-hoc exploratory technique for visualizing clusters of a dataset containing more than two variables. This method was designed as an analogue to principal component analysis (PCA) for handling discrete and categorical data. MCA plotting is no more than an exploratory technique: two points may appear close to each other on a 2D plot, but they may occur far apart if we change our perspective and look at them from a different dimension. The polytomous logistic regression is a further development of the logit regression approach adopted for predicting categorical variables that have more than two levels.
Original languageEnglish
Title of host publicationQuantitative Approaches to the Russian language
ISBN (Print)9781138097155
Publication statusPublished - 2018

Publication series

NameNew Developments in the Quantitative Study of Languages


Dive into the research topics of 'Looking for contextual cues to differentiate modal meanings: a corpus-based study'. Together they form a unique fingerprint.

Cite this