Communication Methods and Measures· 2017Q1
Text Analysis in R
- 269citations
- Q1SCImago
- 2017year
Short summary
R's open-source packages enable advanced computational text analysis, overcoming common software barriers in communication research.
AI-generated from the title and abstract; the full text is not read.
Key points
- Computational text analysis is valuable but difficult due to specialized software needs.
- R statistical software provides an accessible platform for text analysis.
- R's open-source nature fosters a wide range of text analysis packages.
- These R packages simplify advanced text analytics for researchers.
AI-generated from the title and abstract; the full text is not read.
Abstract
Computational text analysis has become an exciting research field with many applications in communication research. It can be a difficult method to apply, however, because it requires knowledge of various techniques, and the software required to perform most of these techniques is not readily available in common statistical software packages. In this teacher’s corner, we address these barriers by providing an overview of general steps and operations in a computational text analysis project, and demonstrate how each step can be performed using the R statistical software. As a popular open-source platform, R has an extensive user community that develops and maintains a wide range of text analysis packages. We show that these packages make it easy to perform advanced text analytics.
The authors' abstract, as published at the source. Communication Methods and Measures, 2017 · DOI ↗
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Field: General Social Sciences
General Social SciencesSocial Sciences