Text analysis with Quanteda: an introduction
DOI:
https://doi.org/10.3145/infonomy.25.040Keywords:
Text analysis, Quanteda, Digital humanities, R, Quantitative analysis, Text mining, Natural language processing, Topic modeling, Data visualization, Computational methodologyAbstract
Quantitative text analysis has become a core methodology within the computational turn in the social sciences and humanities. This paper presents an applied introduction to the Quanteda package for systematic text analysis in the R environment. The aim is to demonstrate, through a tutorial-oriented approach, how to design and implement a basic quantitative text analysis workflow. A set of diary entries by Alexei Navalny is used as a case study to illustrate corpus loading, preprocessing, tokenization, and stopword removal. Results obtained from frequency analysis, word clouds, and topic modeling show Quanteda’s ability to identify relevant lexical and thematic patterns. The paper demonstrates that Quanteda is an accessible and reproducible tool, particularly well suited for teaching contexts and exploratory research in digital humanities.References
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Copyright (c) 2025 Sergio Castro-Cortacero, Nicolás Robinson-García
This work is licensed under a Creative Commons Attribution 4.0 International License.
