Literature DB >> 28699123

The tool for the automatic analysis of lexical sophistication (TAALES): version 2.0.

Kristopher Kyle1, Scott Crossley2, Cynthia Berger2.   

Abstract

This study introduces the second release of the Tool for the Automatic Analysis of Lexical Sophistication (TAALES 2.0), a freely available and easy-to-use text analysis tool. TAALES 2.0 is housed on a user's hard drive (allowing for secure data processing) and is available on most operating systems (Windows, Mac, and Linux). TAALES 2.0 adds 316 indices to the original tool. These indices are related to word frequency, word range, n-gram frequency, n-gram range, n-gram strength of association, contextual distinctiveness, word recognition norms, semantic network, and word neighbors. In this study, we validated TAALES 2.0 by investigating whether its indices could be used to model both holistic scores of lexical proficiency in free writes and word choice scores in narrative essays. The results indicated that the TAALES 2.0 indices could be used to explain 58% of the variance in lexical proficiency scores and 32% of the variance in word-choice scores. Newly added TAALES 2.0 indices, including those related to n-gram association strength, word neighborhood, and word recognition norms, featured heavily in these predictor models, suggesting that TAALES 2.0 represents a substantial upgrade.

Keywords:  Lexical sophistication; Natural language processing; Writing quality

Mesh:

Year:  2018        PMID: 28699123     DOI: 10.3758/s13428-017-0924-4

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


  8 in total

1.  Assisting students' writing with computer-based concept map feedback: A validation study of the CohViz feedback system.

Authors:  Christian Burkhart; Andreas Lachner; Matthias Nückles
Journal:  PLoS One       Date:  2020-06-29       Impact factor: 3.240

2.  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

3.  Sense-aware lexical sophistication indices and their relationship to second language writing quality.

Authors:  Xiaofei Lu; Renfen Hu
Journal:  Behav Res Methods       Date:  2021-08-17

4.  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

5.  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

6.  Lexical Diversity, Lexical Sophistication, and Predictability for Speech in Multiple Listening Conditions.

Authors:  Melissa M Baese-Berk; Shiloh Drake; Kurtis Foster; Dae-Yong Lee; Cecelia Staggs; Jonathan M Wright
Journal:  Front Psychol       Date:  2021-06-18

7.  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

8.  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

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.