Author(s)

Emilio Matricciani

Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB), Politecnico di Milano, Milan, Italy.

We study the short-term memory capacity of ancient readers of the original New Testament written in Greek, of its translations to Latin and to modern languages. To model it, we consider the number of words between any two contiguous interpunctions I_p, because this parameter can model how the human mind memorizes “chunks” of information. Since I_P can be calculated for any alphabetical text, we can perform experiments—otherwise impossible— with ancient readers by studying the literary works they used to read. The “experiments” compare the I_P of texts of a language/translation to those of another language/translation by measuring the minimum average probability of finding joint readers (those who can read both texts because of similar short-term memory capacity) and by defining an “overlap index”. We also define the population of universal readers, people who can read any New Testament text in any language. Future work is vast, with many research tracks, because alphabetical literatures are very large and allow many experiments, such as comparing authors, translations or even texts written by artificial intelligence tools.

Alphabetical Languages, Artificial Intelligence Writing, Greek, Latin, New Testament, Readers Overlap Probability, Short-Term Memory Capacity, Texts, Translation, Words Interval

Matricciani, E. (2023) Short-Term Memory Capacity across Time and Language Estimated from Ancient and Modern Literary Texts. Study-Case: New Testament Translations. Open Journal of Statistics, 13, 379-403. doi: 10.4236/ojs.2023.133019.