Weighted Distribution? Statistical Correlation? Collocations? The Quran as Case Study

Abstract:
Computational Linguistics opens the way to study larger texts and enourmous corpora in a comprehensive way. A prerequisite to proper analysis using computational linguistics is adequate modeling, that is, developing models that adequately capture the intended information contained in a corpus. This task is not only challenging in itself, but there exists also a wide variety of models, each with their specific use, strengths and weaknesses. The paper to be discussed in this seminar is based on work done on the Quran, comprising a series of 5 volumes: The Quran: Key Word Distribution, Correlations and Collocation Frequencies (Gorgias Press, 2022). The aim with the present series is to present key data related to the lexicon of the Quran, in terms of Key Word distribution and lexical associations. As evident from the attached files, each Key Word (KW) – here adjectives, nouns, proper nouns and verbs – in the Quran is presented together with the following key data: Degree of Concentration, Weighted Distribution, Correlations and Collocation Frequencies. The strengths and weaknesses of the models used to establish lexical associations in the Quran shall be discussed at the seminar.

Elie Wardini Higher Seminar, February 2022

The Zoom-ID:
https://stockholmuniversity.zoom.us/j/3440507571
In order to be admitted from the Waiting Room, please register with the convenor of the Higher Seminar, Jaqueline Berndt (jberndt@su.se), if you are NOT affiliated with the Department of Asian and Middle Eastern Studies.