Readability Scores Tied to Topic Distribution, Not Lexical Factors

A new paper published on arXiv suggests that Flesch-Kincaid readability scores for long texts are primarily determined by the topic distribution within the text, rather than other linguistic factors. Researchers found that in the long-text limit, these scores converge to functions of the topic distribution. Experiments on corpora like Brown and the written BNC showed that topic vectors inferred from one half of a document could predict the other half's Flesch-Kincaid Grade Level with significant accuracy. AI

IMPACT Suggests topic modeling may be a more significant factor in text analysis than previously understood.

RANK_REASON Academic paper published on arXiv detailing a new finding about text analysis. [lever_c_demoted from research: ic=1 ai=0.4]

Read on arXiv cs.CL →

• arXiv
• Brown University
• Flesch-Kincaid Grade Level
• Flesch reading ease
• Hugging Face
• National Library of Catalonia

• paper
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