Coh-Metrix: An automated tool for theoretical and applied natural language processing

Danielle McNamara, Arthur C. Graesser

Research output: Chapter in Book/Report/Conference proceedingChapter

45 Scopus citations

Abstract

Coh-Metrix provides indices for the characteristics of texts on multiple levels of analysis, including word characteristics, sentence characteristics, and the discourse relationships between ideas in text. Coh-Metrix was developed to provide a wide range of indices within one tool. This chapter describes Coh-Metrix and studies that have been conducted validating the Coh-Metrix indices. Coh-Metrix can be used to better understand differences between texts and to explore the extent to which linguistic and discourse features successfully distinguish between text types. Coh-Metrix can also be used to develop and improve natural language processing approaches. We also describe the Coh-Metrix Text Easability Component Scores, which provide a picture of text ease (and hence potential challenges). The Text Easability components provided by Coh-Metrix go beyond traditional readability measures by providing metrics of text characteristics on multiple levels of language and discourse.

Original languageEnglish (US)
Title of host publicationApplied Natural Language Processing
Subtitle of host publicationIdentification, Investigation and Resolution
PublisherIGI Global
Pages188-205
Number of pages18
ISBN (Print)9781609607418
DOIs
StatePublished - Dec 1 2011

ASJC Scopus subject areas

  • Computer Science(all)

Fingerprint Dive into the research topics of 'Coh-Metrix: An automated tool for theoretical and applied natural language processing'. Together they form a unique fingerprint.

Cite this