JOURNAL ARTICLE

Using Linguistics and Information Theory to Assess the Diversity, Complexity, and Decoding of Interstellar Message.

  • Published In: Proceedings of the International Astronomical Union, 2024, v. 20, n. S387. P. 35 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Jafari, Saeed; Shaterzadeh Yazdi, Shirin; Karimi, Yadgar; Bigdeli, Parsa 3 of 3

Abstract

This abstract explores the application of quantitative information theory measures and linguistic features to analyze animal communication systems and extends this methodology to contemplate the possibilities of interstellar communication as a part of CETI practice. We will assess some early findings by using information theory on social species with sophisticated acoustic communication abilities, such as bottlenose dolphins and humpback whales (Hanser, Sean F., et al.) as well as birds, as examples of how the complex interplay between notions, data, and misinterpretations can become established as reliable knowledge and cognition about and understanding of an ETI civilization and culture. The study also looks into the potential implications of extraterrestrial contact. Given the diversity of language instances in Earth's evolutionary history, we discuss the choice of syntactic complexity of an "intelligent message" for potential alien civilizations. The central point of this paper is to examine the advantages and limitations of acoustic and visual communication, considering linguistical and mathematical constraints that may apply universally. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Proceedings of the International Astronomical Union. 2024/12, Vol. 20, Issue S387, p35
  • Document Type:Conference Paper/Materials
  • Subject Area:Literature and Writing
  • Publication Date:2024
  • ISSN:1743-9213
  • DOI:10.1017/S1743921325000365
  • Accession Number:190966736
  • Copyright Statement:Copyright of Proceedings of the International Astronomical Union is the property of Cambridge University Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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