An introduction to quantitative text analysis for linguistics : reproducible research using R

• Main Author: Francom, Jerid
• Format: eBook Book
• Language: English
• Published: Oxford Routledge 2025; Taylor & Francis
• Subjects: applied linguistics; Biography, Literature and Literary studies; Computational linguistics > Statistical methods; data analysis; data literacy; develop research skills; Jerid Francom; Language and Linguistics; Language Arts & Disciplines; Language teaching and learning; Language teaching theory and methods; Linguistics; Literature: history and criticism; pedagogical; programming skills; quantitative text analysis; R (Computer program language); R programming; real-world datasets; Reference, Information and Interdisciplinary subjects; reproducible; Research and information: general; Research methods: general; statistical methods; statistics for linguists; text analysis; Text data mining; Textbook
• ISBN: 1032494263; 9781032494265; 9781040153444; 1040153453; 1032494271; 1003393764; 9781032494272; 1040153445; 9781040153451; 9781003393764
• DOI: 10.4324/9781003393764

An Introduction to Quantitative Text Analysis for Linguistics: Reproducible Research Using R is a pragmatic textbook that equips students and researchers with the essential concepts and practical programming skills needed to conduct quantitative text analysis in a reproducible manner. Designed for undergraduate students and those new to the field, this book assumes no prior experience with statistics or programming, making it an accessible resource for anyone embarking on their journey into quantitative text analysis. Through a pedagogical approach which emphasizes intuitive understanding over technical details, readers will gain data literacy by learning to identify, interpret, and evaluate data analysis procedures and results. They will also develop research skills, enabling them to design, implement, and communicate quantitative text analysis projects effectively. The book places a strong emphasis on programming skills, guiding readers through interactive lessons, tutorials, and lab activities using the R programming language and real-world datasets. This practical textbook is enriched with features that facilitate learning, including thought and practical exercises, a companion website that includes programming demonstrations to develop and augment readers’ recognition of how programming strategies are implemented, and a GitHub repository that contains both a set of interactive R programming lessons and lab exercises, which guide readers through practical hands-on programming applications. This textbook is an essential companion to any linguist looking to learn how to incorporate quantitative data analysis into their work. The Open Access version of this book, available at http://www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND) 4.0 license.