Matricciani, E. Linguistic Communication Channels Reveal Connections between Texts: The New Testament and Greek Literature. Information2023, 14, 405.
Matricciani, E. Linguistic Communication Channels Reveal Connections between Texts: The New Testament and Greek Literature. Information 2023, 14, 405.
Matricciani, E. Linguistic Communication Channels Reveal Connections between Texts: The New Testament and Greek Literature. Information2023, 14, 405.
Matricciani, E. Linguistic Communication Channels Reveal Connections between Texts: The New Testament and Greek Literature. Information 2023, 14, 405.
Abstract
We study two fundamental linguistic channels ‒ the Sentences and the Interpunctions channels ‒ and show they can reveal deeper connections between texts. The theory applied does not follow the actual paradigm of linguistic studies. As study‒case, we consider the Greek New Testament, with the purpose of determining mathematical connections between its texts and possible differences in writing style (mathematically defined) of writers, and in reading skill required to their readers. The analysis is based on deep‒language parameters and communication/information theory. To set the New Testament texts in the larger Greek Classical Literature, we consider texts written by Aesop, Polybius, Flavius Josephus and Plutarch. The results largely confirm what scholars have found about the New Testament texts giving, therefore, credibility to the theory. The gospel according to John is very similar to Fables written by Aesop. Surprisingly, the Epistle to the Hebrews and Apocalypse, are each other “photocopy” in the two linguistic channels, and not linked to all other texts. These two texts deserve further study by historians of the early Christian Church Literature at the level of meaning, readers and possible Old Testament texts which might have influenced them. The theory can guide scholars to study any literary corpus.
Keywords
Apocalypse; Deep‒language; Greek New Testament; Greek Classical Literature; Epistle to the Hebres; Interpunctions; Likeness index; Linguistic channels; Sentences; Signal‒to‒noise ratio; Vectors;
Subject
Computer Science and Mathematics, Applied Mathematics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
