TY - BOOK ID - 101210631 TI - Natural language processing for corpus linguistics PY - 2022 SN - 1009070444 1009083740 1009083023 1009074431 9781009070447 9781009074438 PB - Cambridge : Cambridge University Press, DB - UniCat KW - Corpora (Linguistics) KW - Natural language processing (Computer science) KW - Data processing. KW - Artificial intelligence KW - Electronic data processing KW - Human-computer interaction KW - Semantic computing KW - NLP (Computer science) KW - Linguistic analysis (Linguistics) KW - Corpus-based analysis (Linguistics) KW - Corpus linguistics KW - Data processing UR - https://www.unicat.be/uniCat?func=search&query=sysid:101210631 AB - 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. These computational methods are becoming increasingly important as corpora grow too large for more traditional types of linguistic analysis. We draw on five case studies to show how and why to use computational methods, ranging from usage-based grammar to authorship analysis to using social media for corpus-based sociolinguistics. Each section is accompanied by an interactive code notebook that shows how to implement the analysis in Python. A stand-alone Python package is also available to help readers use these methods with their own data. Because large-scale analysis introduces new ethical problems, this Element pairs each new methodology with a discussion of potential ethical implications. ER -