Analyzing Discourse Processing Using a Simple Natural Language Processing Tool

Scott A. Crossley, Laura K. Allen, Kristopher Kyle, Danielle S. McNamara

Research output: Contribution to journalArticlepeer-review

53 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)511-534
Number of pages24
JournalDiscourse Processes
Issue number5-6
Publication statusPublished - 2014 Jul

Bibliographical note

Funding Information:
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.

All Science Journal Classification (ASJC) codes

  • Communication
  • Language and Linguistics
  • Linguistics and Language


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