textNet is a set of tools that uses part-of-speech tagging and dependency parsing to generate semantic networks from text data.
To be used in the main project repo: https://github.com/ucd-cepb/textNet
Network extraction from documents has typically required manual coding. Furthermore, existing network extraction methods that use co-occurrence leave a vast amount of data on the table, namely, the rich edge attribute data and directionality of each verb phrase defining the particular relationship between two entities, and the respective roles of the entity nodes involved in that verb phrase. We present an R package, textNet, designed to enable directed, multiplex, multimodal network extraction from text documents through syntactic dependency parsing, in a replicable, automated fashion for collections of arbitrarily long documents. The textNet package facilitates the automated analysis and comparison of many documents, based on their respective network characteristics. Its flexibility allows for any desired entity categories, such as organizations, geopolitical entities, dates, or custom-defined categories, to be preserved.
See vignettes/paper.pdf for an overview of the package functionality and potential use cases.
To demo the package, see vignettes/textNet_vignette_2024.pdf for a reproducible example that transforms raw text data into event networks.
Clone this repo and install with devtools from within project directory
devtools::install()
or using devtools::install_github():
devtools::install_github('ucd-cepb/textNet')
Make changes to the code, then run devtools::load_all() and test them.
To update documentation and NAMESPACE file devtools::document().
To reinstall the package: devtools::install()
Elise Zufall ezufall at ucdavis dot edu
Tyler Scott tascott at ucdavis dot edu