Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/129014
Title: Beyond lexical frequencies: using R for text analysis in the digital humanities
Authors: Arnold, Taylor
Ballier, Nicolas
Lissón Hernández, Paula José 
Tilton, Lauren
UNESCO Clasification: 5701 Lingüística aplicada
Keywords: Digital humanities
Text mining
R
Text interoperability
Issue Date: 2019
Journal: Language Resources and Evaluation 
Abstract: This paper presents a combination of R packages—user contributed toolkits written in a common core programming language—to facilitate the humanistic investigation of digitised, text-based corpora.Our survey of text analysis packages includes those of our own creation (cleanNLP and fasttextM) as well as packages built by other research groups (stringi, readtext, hyphenatr, quanteda, and hunspell). By operating on generic object types, these packages unite research innovations in corpus linguistics, natural language processing, machine learning, statistics, and digital humanities. We begin by extrapolating on the theoretical benefits of R as an elaborate gluing language for bringing together several areas of expertise and compare it to linguistic concordancers and other tool-based approaches to text analysis in the digital humanities. We then showcase the practical benefits of an ecosystem by illustrating how R packages have been integrated into a digital humanities project. Throughout, the focus is on moving beyond the bag-of-words, lexical frequency model by incorporating linguistically-driven analyses in research.
URI: http://hdl.handle.net/10553/129014
ISSN: 1574-020X
DOI: 10.1007/s10579-019-09456-6
Source: Language Resources and Evaluation [1574-020X], vol. 53, p. 707–733
Appears in Collections:Artículos
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