A whale of a tool: navigating texts with Voyant Tools
As a corpus linguist, I happen to teach my students how to use R for text analysis. However, due to the steep learning curve associated with R, I sometimes need to provide more accessible,...
A corpus linguist's research notebook
As a corpus linguist, I happen to teach my students how to use R for text analysis. However, due to the steep learning curve associated with R, I sometimes need to provide more accessible,...
In a previous post, I provided two frequency lists without revealing the scripts to make them. This post explains how to create word frequency lists (lemmatized and unlemmatized) from the BNC 2014 (spoken), using...
Each academic year, I lead my Master’s students in English linguistics on an intellectual journey that traces the evolution from traditional structuralist semantics to contemporary cognitive linguistics. A significant moment of this journey is...
As a follow-up to my previous post (POS-tagging in R with UDPipe), I explore the udpipe package further, focusing this time on dependency parsing. Dependency parsing is a process of analyzing the grammatical structure...
POS stands for “part-of-speech” (i.e. the grammatical nature of a word). POS tagging is the process of assigning a part-of-speech (such as noun, verb, adverb, adjective, determiner, etc.) to each word in a given...
In Corpus Linguistics and Statistics with R, I showed how to make a word cloud from a text file (Section 6.3). A word cloud is a user-friendly way of representing a frequency list graphically....
Every year in November, France eagerly awaits the Beaujolais Nouveau and the new edition of the reference dictionary of French: Le Robert. As New York Times wine critic Eric Asimov wrote: “Beaujolais is a far...
Martin Schweinberger and Michael Haugh (University of Queensland, Australia) invited me to to give a LADAL Opening Webinar Series 2021 talk. I felt quite honored to be part of a prestigious panel of fellow...
The 11th International Conference on Construction Grammar (ICCG11) takes place from Wednesday 18 till Friday 20 August 2021. It covers a broad range of topics related to Construction Grammar approaches to language. My talk...
L’Ecole Doctorale 139 de l’Université Paris Nanterre organise un séminaire pluridisciplinaire thématique. Cette année (2020-2021), le thème imposé est “Preuves et présomptions”. Avec Sylvain Kahane, professeur en sciences du langage à l’Université Paris Nanterre,...
Multidimensional scaling (MDS) is a very popular multivariate exploratory approach because it is relatively old, versatile, and easy to understand and implement. It is used to visualize distances in multidimensional maps (in general: two-dimensional...
The dplyr package is based on a data manipulation ‘grammar’. This grammar provides a consistent set of ‘verbs’ that solve the most common data manipulation tasks. I illustrate five of these ‘verbs’: filter(), arrange(), select(), mutate(), and summarise().
The tidyr package is part of the tidyverse. As its name indicates, it is meant to help you create tidy data or tidy messy data according to the tidy data principles: each variable forms a column; each observation forms a row; each type of observational unit forms a table. This post illustrates how to tidy a data set in R using two tidyr functions: pivot_longer() and separate().
Since the publication of my book on corpus linguistics with R, many colleagues have asked me if I was planning to switch the whole code to the tidy style (some of the code in the book makes use of some tidyverse packages. If you want to know my answer, please read on.
In a previous post, I showed how to use the igraph package for R to plot a graph of the nominal collocates of the verbs hoard and stockpile in the Coronavirus Corpus (Davies, 2020)....