Text Analytics for Corpus Linguistics and Digital Humanities: Simple R Scripts and Tools

Do you want to gain a deeper understanding of how big tech analyses and exploits our text data; or investigate how political parties differ by analysing textual styles; associations and trends in documents? Or create a map of a text collection and write a simple QA system yourself? This book explores how to apply state-of-the-art text analytics methods to detect and visualise phenomena in text data. Solidly based on methods from corpus linguistics; natural language processing; text analytics and digital humanities; this book shows readers how to conduct experiments with their own corpora and research questions; underpin their theories; quantify the differences and pinpoint characteristics. Case studies and experiments are detailed in every chapter using real-world and open access corpora from politics; World English; history; and literature. The results are interpreted and put into perspective; pitfalls are pointed out; and necessary pre-processing steps are demonstrated. This book also demonstrates how to use the programming language R; as well as simple alternatives and additions to R; to conduct experiments and employ visualisations by example; with extensible R-code; recipes; links to corpora; and a wide range of methods. The methods introduced can be used across texts of all disciplines; from history or literature to party manifestos and patient reports.