Mary Wollstonecraft and Influence - Preprocessed Datadoi:10.48349/ASU/GPDIR5ASU Library Research Data Repository2020-11-052Caddy, Scott; Simeone, Michael, 2020, "Mary Wollstonecraft and Influence - Preprocessed Data", https://doi.org/10.48349/ASU/GPDIR5, ASU Library Research Data Repository, V2, UNF:6:OQj5GZyoTEE3yp9MjBJs/g== [fileUNF]Mary Wollstonecraft and Influence - Preprocessed Datadoi:10.48349/ASU/GPDIR5Caddy, ScottSimeone, Michael2018-04-19ASU Library Research Data RepositorySimeone, MichaelHarp, Matthew2020-11-05Arts and HumanitiesComputer and Information SciencePreprocessing steps for this topic modeling are laid out in this dataset. It contains a stopword list, additions made to the stop word list, plus steps taken to clean each text within the corpus. Original stopword list obtained at GitHub: <a href="https://github.com/fozziethebeat/S-Space/blob/master/data/english-stop-words-large.txt">https://github.com/fozziethebeat/S-Space/blob/master/data/english-stop-words-large.txt </a> For this project, preprocessing was a much less straightforward step than the collocate/concordance project from Fall 2017. Most of the preprocessing was done by myself [Scott Caddy] via SublimeText. Segmenting of items in the corpus was done via the TopicModelingTool settings. What I have here is a step-by-step process attempted over several weeks as I learned more about the TopicModelingTool, topic modeling, and how to interpret the results. A large part of my preprocessing came from doing topic modeling "runs" and modying my stopword list according to results. Hopefully, this component can show how I continued to hone preprocessing, based on feedback from my peers, instructor, and reading papers on topic modeling.textual dataCaddy, S., & Simeone, M. (2020, October 31). Preprocessed Data. Retrieved from osf.io/brx2qCaddy, S., & Simeone, M. (2020, October 31). Preprocessed Data. Retrieved from osf.io/brx2qMWC Metadata - NEW 3.29.18 - 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