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This Element applies the new approach of corpus-assisted multimodal discourse analysis in relation to how news values are discursively constructed through language and photographs. Using case studies of news from China and Australia, the Element presents a cross-linguistic comparison of news values in national day reporting.

This Element explores ways to improve how we approach linguistic research questions with quantitative corpus data. We introduce and illustrate the major steps in the research process, and provide suggestions for improvements that will help researchers make quantitative corpus-based research more language focused and linguistically informative.

This Element explores interdisciplinarity in academic writing by describing the ways in which disciplines interact when forming interdisciplinary fields and how language reflects (and is reflected by) these interactions. The methodology employed combines analysis of quantitative data with their qualitative interpretation by means of close reading.

This Element provides a basic introduction to sentiment analysis, aimed at helping students and professionals in corpus linguistics to understand what sentiment analysis is, how it is conducted, and where it can be applied.

Corpus analysis can be expanded and scaled up by incorporating computational methods from natural language processing. This Element shows how text classification and text similarity models can extend our ability to undertake corpus linguistics across very large corpora.