Literature DB >> 26416138

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

Scott A Crossley1, Kristopher Kyle2, Danielle S McNamara2.   

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.

Keywords:  Coherence; Cohesion; Natural language processing; Text difficulty; Writing quality

Mesh:

Year:  2016        PMID: 26416138     DOI: 10.3758/s13428-015-0651-7

Source DB:  PubMed          Journal:  Behav Res Methods        ISSN: 1554-351X


  14 in total

1.  A large-scaled corpus for assessing text readability.

Authors:  Scott Crossley; Aron Heintz; Joon Suh Choi; Jordan Batchelor; Mehrnoush Karimi; Agnes Malatinszky
Journal:  Behav Res Methods       Date:  2022-03-16

2.  Validity of a Computational Linguistics-Derived Automated Health Literacy Measure Across Race/Ethnicity: Findings from The ECLIPPSE Project.

Authors:  Dean Schillinger; Renu Balyan; Scott Crossley; Danielle McNamara; Andrew Karter
Journal:  J Health Care Poor Underserved       Date:  2021-05

3.  Divergent semantic integration (DSI): Extracting creativity from narratives with distributional semantic modeling.

Authors:  Dan R Johnson; James C Kaufman; Brendan S Baker; John D Patterson; Baptiste Barbot; Adam E Green; Janet van Hell; Evan Kennedy; Grace F Sullivan; Christa L Taylor; Thomas Ward; Roger E Beaty
Journal:  Behav Res Methods       Date:  2022-10-17

4.  On Elementary Affective Decisions: To Like Or Not to Like, That Is the Question.

Authors:  Arthur Jacobs; Markus J Hofmann; Annette Kinder
Journal:  Front Psychol       Date:  2016-11-24

Review 5.  The Next Frontier in Communication and the ECLIPPSE Study: Bridging the Linguistic Divide in Secure Messaging.

Authors:  Dean Schillinger; Danielle McNamara; Scott Crossley; Courtney Lyles; Howard H Moffet; Urmimala Sarkar; Nicholas Duran; Jill Allen; Jennifer Liu; Danielle Oryn; Neda Ratanawongsa; Andrew J Karter
Journal:  J Diabetes Res       Date:  2017-02-07       Impact factor: 4.011

6.  Using natural language processing and machine learning to classify health literacy from secure messages: The ECLIPPSE study.

Authors:  Renu Balyan; Scott A Crossley; William Brown; Andrew J Karter; Danielle S McNamara; Jennifer Y Liu; Courtney R Lyles; Dean Schillinger
Journal:  PLoS One       Date:  2019-02-22       Impact factor: 3.240

7.  Predicting the readability of physicians' secure messages to improve health communication using novel linguistic features: Findings from the ECLIPPSE study.

Authors:  Scott A Crossley; Renu Balyan; Jennifer Liu; Andrew J Karter; Danielle McNamara; Dean Schillinger
Journal:  J Commun Healthc       Date:  2020-09-24

8.  Recognizing hotspots in Brief Eclectic Psychotherapy for PTSD by text and audio mining.

Authors:  Sytske Wiegersma; Mirjam J Nijdam; Arjan J van Hessen; Khiet P Truong; Bernard P Veldkamp; Miranda Olff
Journal:  Eur J Psychotraumatol       Date:  2020-03-17

9.  Developing and Testing Automatic Models of Patient Communicative Health Literacy Using Linguistic Features: Findings from the ECLIPPSE study.

Authors:  Scott A Crossley; Renu Balyan; Jennifer Liu; Andrew J Karter; Danielle McNamara; Dean Schillinger
Journal:  Health Commun       Date:  2020-03-02

10.  Employing computational linguistics techniques to identify limited patient health literacy: Findings from the ECLIPPSE study.

Authors:  Dean Schillinger; Renu Balyan; Scott A Crossley; Danielle S McNamara; Jennifer Y Liu; Andrew J Karter
Journal:  Health Serv Res       Date:  2020-09-23       Impact factor: 3.734

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