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Abstract
Natural language processing (NLP) provides a powerful approach for discourse processing researchers. However, there remains a notable degree of hesitation by some researchers to consider using NLP, at least on their own. The purpose of this article is to introduce and make available a simple NLP (SiNLP) tool. The overarching goal of the article is to proliferate the use of NLP in discourse processing research. The article also provides an instantiation and empirical evaluation of the linguistic features measured by SiNLP to demonstrate their strength in investigating constructs of interest to the discourse processing community. Although relatively simple, the results of this analysis reveal that the tool is quite powerful, performing on par with a sophisticated text analysis tool, Coh-Metrix, on a common discourse processing task (i.e., predicting essay scores). Such a tool could prove useful to researchers interested in investigating features of language that affect discourse production and comprehension.
Acknowledgments
We thank Mark Johnson for providing an early draft of his book, Essential Python for Corpus Linguistics, to be used in an NLP class at Georgia State University. The class and the book acted as an inspiration for the development of SiNLP. We also thank Mary Sellers for her design of the SiNLP icon.
FUNDING
This research was supported in part by the Institute for Education Sciences (IES R305A080589 and IES R305G20018-02). Ideas expressed in this material are those of the authors and do not necessarily reflect the views of the IES.