Corpus Linguistics

The course is structured into three main modules: A, B, and C.

Module A - Introduction to Corpus Linguistics
Module A provides a general introduction to corpus linguistics, presenting its main theoretical, methodological and operational foundations. The module will discuss the criteria that define a linguistic corpus and will introduce key issues involved in corpus design, description and use.
Attention will be given to the relationship between corpora, research questions and linguistic evidence, with reference to different types of corpora and to some of the methodological choices involved in corpus-based research. The module will also provide an overview of the development of corpus linguistics as a discipline and of its role in contemporary language studies.
An operational introduction to Sketch Engine will also be included. Interactive activities in Module A will guide students in observing linguistic data, comparing intuition and evidence, reflecting on corpus definitions and beginning to use corpus tools in a guided way.
Module B - Quantitative Methods for Corpus Data Analysis
Module B introduces students to the main conceptual, quantitative and operational tools for analysing data derived from linguistic corpora. The module presents basic notions such as token, type and lemma, lexical variety, type-token ratio, standardised and moving average type-token ratio, absolute and relative frequency, and normalisation.
The module also introduces the distribution of frequencies, Zipf's Law, the notions of collocations, node and collocate, span, bigrams, observed and expected frequency, and the main association measures used to describe co-occurrences between linguistic items, including T-score, Mutual Information and LogDice. The concept of keyness will also be addressed, with particular attention to the relationship between focus corpus and reference corpus, keywords and terms.
The aim of the module is to equip students with the tools necessary to understand and critically interpret quantitative results produced by corpus analysis software.
Interactive activities in Module B include guided exercises and inductive tasks. Students will work on token/type counts, lexical variety, relative frequency and normalisation, wordlists and rank/frequency graphs, collocations, association measures and keyness.
Module C - Practical Applications
Module C is dedicated to the application of corpus linguistics principles and methods. The module focuses on selected guided activities and mini-project work designed to consolidate the analytical skills developed in the previous modules.
The module introduces students to the formulation of research questions that are compatible with a corpus-based approach, that is, questions that can be addressed through the analysis of linguistic data observable in a corpus. Students will be guided to reflect on the relationship between research question, corpus selection, data type, analytical method and limits of interpretation.
The goal of the module is to foster the ability to apply corpus linguistics tools critically, while keeping the analysis anchored to observable linguistic evidence.