Synthetically generated text can help researchers address common issues in supervised text analysis.
Much of my work involves improving large-scale systems to extract political events from text (see code from our NSF project on the subject here). These systems are designed for full production use over many hundreds of sources both daily and for the past in many dozens of event categories, including protests, armed conflict, statements, arrests, and humanitarian aid.
Reproducible methods like knitr and version control using git are on their way toward being standard for academic code, even in social science disciplines such as political science. knitr, Rmarkdown, and Jupyter notebooks make it easy to verify that your findings and figures come from the most recent version of your code and that it runs without errors.
This tutorial covers how to create event data from a new set of text using existing Open Event Data Alliance tools. After going through it, you should be able to use the OEDA event data pipeline for your own projects with your own text.