Readability Indices Do Not Say It All on a Text Readability

Abstract

We propose a universal readability index, GU, applicable to any alphabetical language and related to cognitive psychology, the theory of communication, phonics and linguistics. This index also considers readers’ short-term-memory processing capacity, here modeled by the word interval IP, namely, the number of words between two interpunctions. Any current readability formula does not consider Ip, but scatterplots of Ip versus a readability index show that texts with the same readability index can have very different Ip, ranging from 4 to 9, practically Miller’s range, which refers to 95% of readers. It is unlikely that IP has no impact on reading difficulty. The examples shown are taken from Italian and English Literatures, and from the translations of The New Testament in Latin and in contemporary languages. We also propose an extremely compact formula, relating the capacity of human short-term memory to the difficulty of reading a text. It should synthetically model human reading difficulty, a kind of “footprint” of humans. However, further experimental and multidisciplinary work is necessary to confirm our conjecture about the dependence of a readability index on a reader’s short-term-memory capacity.

Linguistic Communication Channels Reveal Connections between Texts: The New Testament and Greek Literature

“…[12][13][14][15][16][17][18] report results not based on mathematical analyses of texts-as our theory does-and when a mathematical approach is used, as in Refs. , most of these studies consider neither Shannon's communication theory, nor the fundamental connection that some linguistic variables seem to have with reading ability and short-term memory (STM) capacity [1][2][3][4][5][6][7][8]. In fact, these studies are mainly concerned with automatic translations, not with a high-level direct response of human readers, as our theory is.…”

“…In recent papers [1][2][3][4][5][6][7][8], we have developed a general theory on the deep-language mathematical structure of literary texts (or any long text), including their translation. The theory is based on linguistic communication channels-suitably defined-always contained in texts and based on the theory of regression lines [9,10] and Shannon's communication and information theory [11].…”

“…In addition to the total number of characters, words, sentences, and interpunctions (punctuation marks) of a text, the linguistic parameters considered in our theory are the number of words n W per chapter, the number of sentences n S per chapter, and the number of interpunctions per chapter n I . Instead of referring to chapters, the analysis can refer to any chosen subdivision of a literary text, large enough to provide reliable statistics, such as a few hundred words [1][2][3][4][5][6][7][8].…”

“…In Ref. [6] we have defined a universal readability index, applicable to any alphabetical language, by including the readers' STM capacity, modeled by I P ; in Ref. [7] we have studied the STM capacity across time and language, and in Ref.…”

“…Like in Refs. [1][2][3][4][5][6][7][8]53], samples were statistically weighted with the fraction of total words; therefore, in Matthew-which contains 18121 total words-Chapter 5, for example, has 824 words, and therefore, its weight is 824/18121 = 0.0455, not 1/128 = 0.0078. This choice is mandatory to avoid that a short chapter (or, in general, a short text) affects the statistical results like a long one.…”