A large-scaled corpus for assessing text readability

• Published in: Behavior research methods Vol. 55; no. 2; pp. 491 - 507
• Main Authors: Crossley, Scott, Heintz, Aron, Choi, Joon Suh, Batchelor, Jordan, Karimi, Mehrnoush, Malatinszky, Agnes
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.02.2023; Springer Nature B.V
• Subjects: Behavioral Science and Psychology; Cognitive Psychology; Comprehension; Humans; Psychology; Publishing; Reading; Reproducibility of Results; Writing; Natural language processing; Readability; Corpus linguistics; Readability formulas
• ISSN: 1554-3528; 1554-351X; 1554-3528
• DOI: 10.3758/s13428-022-01802-x

This paper introduces the CommonLit Ease of Readability (CLEAR) corpus, which provides unique readability scores for ~ 5000 text excerpts along with information about the excerpt’s year of publishing, genre, and other metadata. The CLEAR corpus will provide researchers interested in discourse processing and reading with a resource from which to develop and test readability metrics and to model text readability. The CLEAR corpus includes a number of improvements in comparison to previous readability corpora including size, breadth of the excerpts available, which cover over 250 years of writing in two different genres, and unique readability criterion provided for each text based on teachers’ ratings of text difficulty for student readers. This paper discusses the development of the corpus and presents reliability metrics for the human ratings of readability.