Derivation of New Readability Formulas (Automated Readability Index, Fog Count and Flesch Reading Ease Formula) for Navy Enlisted Personnel

By P. Kincaid, R. P. Fishburne, R. L. Rogers, B. Chissom. 1975

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Repairing the Cracked Foundation: A Survey of Obstacles in Evaluation Practices for Generated Text (2022, methodology): “…that could be useful for tasks like simplification is the readability of text, which could be measured using scales such as the ones proposed by Kincaid et al. (1975) or Ambati et al. (2016). van der Lee et al. point out that the relationship between these objective measures and subjective…”
Explainable Recommendation: A Survey and New Perspectives (2018, background): “[2018a]), news/articles (Kraus [2016]), music (Celma [2010]), movie (Tintarev and Masthoff [2008], Nanou et al.”
Using Simpson's Paradox to Discover Interesting Patterns in Behavioral Data (2018, background): “Features include the numbers of words, hyperlinks, and lines of code the answer contains, and its Flesch readability score (Kincaid et al. 1975).”
Explainable Automated Fact-Checking for Public Health Claims (2020, neutral): “Claims from our dataset have a mean Flesch-Kincaid reading ease score of 59.1, which corresponds to a 10th-12th grade reading level and fairly difﬁcult to read.”
Optimizing Statistical Machine Translation for Text Simplification (2016, methodology): “Since the text simpliﬁcation task aims at improving readability, we include the Flesch-Kincaid Index ( FK ) which estimates the readability of text using cognitively motivated features (Kincaid et al., 1975): with a lower value indicating higher readability.”
A Reinforcement Learning Approach for Adaptive Single- and Multi-Document Summarization (2015, methodology): “Finally, we make use of higher level analysis, such as the readability score (Flesch, 1948; Kincaid et al., 1975).”
Winning Arguments: Interaction Dynamics and Persuasion Strategies in Good-faith Online Discussions (2016, methodology): “Finally, we compute Flesch-Kincaid grade level [26] to represent readability.”
Predicting the “helpfulness” of online consumer reviews (2017, methodology): “The explanatory variables were Polarity , Subjectivity , Noun , Adjective , Verb , Flesch_Reading_Ease , Dale_Chall Readability , Difficult_Words , Length , Set_length , Stop_count , Wrong_words , One_letter_words , Two_letter_words , Longer_letter_words , Lex_diversity , Entropy , and Rating .”
EASSE: Easier Automatic Sentence Simplification Evaluation (2019, methodology): “FKGL (Kincaid et al., 1975)).”
Creating a Progress–Monitoring System in Reading for Middle–School Students: Tracking Progress toward Meeting High–Stakes Standards (2010, methodology): “For the remaining passages, readability levels were calculated using both the DRP (Touchstone Applied Science and Associates, 2006) and Flesch-Kincaid (Kincaid et al., 1975).”
Problems in Current Text Simplification Research: New Data Can Help (2015, background): “In addition, readability is widely studied and can be automatically estimated (Kincaid et al., 1975; Pitler and Nenkova, 2008; Petersen and Ostendorf, 2009).”