Nikki Garlic

Using R to Wrangle and Analyze Unstructured Text in Federal Court Case Dockets

In 2020, the COVID-19 pandemic propelled U.S. federal courts into extensive use of video ('zoom') hearings. Because of the limited prior use of this hearing modality, the number and characteristics of these hearings is not readily available as downloadable statistical data. This makes the study of these hearings difficult for academic researchers. To overcome this challenge, this project developed an R script for wrangling and analyzing the unstructured text found in US federal court case docket 'minute entry' fields. In the federal court utilized in this project, the minute entry field consists of free-form text written by court staff with details about the type of hearing, its modality, and a summary of what occurred. Combined with case data, such as the assigned judge and type of case, the minute entry text can be used to paint more complex pictures of hearing processes and practices both pre- and post-2020. This presentation overviews this easily-adaptable script for wrangling and analyzing the minute entry text data using html dockets and regex. It is part of the author's dissertation research on the social justice implications of video hearings.

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