The tool for the automatic analysis of text cohesion (TAACO): Automatic assessment of local, global, and text cohesion

Scott A. Crossley, Kristopher Kyle, Danielle McNamara

Research output: Contribution to journalArticle

37 Citations (Scopus)

Abstract

This study introduces the Tool for the Automatic Analysis of Cohesion (TAACO), a freely available text analysis tool that is easy to use, works on most operating systems (Windows, Mac, and Linux), is housed on a user’s hard drive (rather than having an Internet interface), allows for the batch processing of text files, and incorporates over 150 classic and recently developed indices related to text cohesion. The study validates TAACO by investigating how its indices related to local, global, and overall text cohesion can predict expert judgments of text coherence and essay quality. The findings of this study provide predictive validation of TAACO and support the notion that expert judgments of text coherence and quality are either negatively correlated or not predicted by local and overall text cohesion indices, but are positively predicted by global indices of cohesion. Combined, these findings provide supporting evidence that coherence for expert raters is a property of global cohesion and not of local cohesion, and that expert ratings of text quality are positively related to global cohesion.

Original languageEnglish (US)
JournalBehavior Research Methods
DOIs
StateAccepted/In press - Sep 28 2015

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Cohesion

Keywords

  • Coherence
  • Cohesion
  • Natural language processing
  • Text difficulty
  • Writing quality

ASJC Scopus subject areas

  • Psychology(all)
  • Psychology (miscellaneous)
  • Experimental and Cognitive Psychology
  • Arts and Humanities (miscellaneous)
  • Developmental and Educational Psychology

Cite this

The tool for the automatic analysis of text cohesion (TAACO) : Automatic assessment of local, global, and text cohesion. / Crossley, Scott A.; Kyle, Kristopher; McNamara, Danielle.

In: Behavior Research Methods, 28.09.2015.

Research output: Contribution to journalArticle

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