Book review of Dunn (2022): Natural Language Processing for Corpus Linguistics
What is it about?
The book "Natural Language Processing for Corpus Linguistics" by Dunn (2022) is a practical guide published in the Cambridge Elements in Corpus Linguistics series. With a strong focus on hands-on learning, it features 20 interactive Python labs covering text classification, similarity models, and validation/visualization techniques. The book introduces crucial NLP concepts, including vector space representations and word embeddings, while emphasizing ethical considerations in language analysis. While it simplifies certain underlying assumptions and aspects of language processing, the book serves as a valuable resource for both experts and students in corpus linguistics, providing practical insights into computational complexity and addressing real-world challenges in natural language processing.
Why is it important?
A review of books aimed at the intersection of NLP and linguistics is important to allow people interested in understanding what is happening in the textual AI/ML space to understand how to best approach understanding these fields, contributing to them in an ethical manner, and understand their interdisciplinary connection. By assessing the book's practicality, accessibility, underlying assumptions, and ethical considerations, the review guides linguists and researchers in navigating the complexities of natural language processing. The review serves as a valuable resource for individuals seeking to understand the societal implications of incorporating computational linguistics into their research and analytical practices.