MEASURING THE LINGUISTIC EFFICIENCY BY MEANS OF SHANNON ENTROPY AND ZIPF’S LAW ON DIFFERENT TEXT GENRES

Authors

  • Ambreen Zehra Rizvi Assistant Professor, Faculty of Engineering, Science & Technology, Hamdard University Main Campus, Karachi, Pakistan.
  • Nazra Zahid Shaikh Senior Lecturer, Department of English, Faculty of Social Sciences and Humanities, Hamdard University Main Campus, Karachi, Pakistan.

Abstract

This study examines how efficient language is in different genres—academic papers, news reports, fiction, and tweets—based on Shannon entropy and Zipf’s Law between COCA and Twitter. Salient observations are that academic text exhibits the most extreme entropy (H = 10.2 bits, indicative of dense information), that social media data is almost Zipfian (α = −1.03 ), and that fictional text reaches a nominal point of compromise between creativity and readability. This research investigates lexical diversity, word frequencies distributions, and compression efficiency to show how various genres achieve maximal communication optimization.

Keywords: Shannon entropy, Zipf’s Law, linguistic efficiency, genre analysis, computational linguistics

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Published

2025-06-27

How to Cite

Ambreen Zehra Rizvi, & Nazra Zahid Shaikh. (2025). MEASURING THE LINGUISTIC EFFICIENCY BY MEANS OF SHANNON ENTROPY AND ZIPF’S LAW ON DIFFERENT TEXT GENRES. Journal for Current Sign, 3(2), 893–911. Retrieved from http://currentsignjournal.com/index.php/JCS/article/view/210

Issue

Vol. 3 No. 2 (2025): Journal for Current Sign

Section

Articles