Paper Info
Title
Complexity measurement of natural and artificial languages.
Abstract
We compared entropy for texts written in natural languages English, Spanish and artificial languages computer software based on a simple expression for the entropy as a function of message length and specific word diversity. Code text written in artificial languages showed higher entropy than text of similar length expressed in natural languages. Spanish texts exhibit more symbolic diversity than English ones. Results showed that algorithms based on complexity measures differentiate artificial from natural languages, and that text analysis based on complexity measures allows the unveiling of important aspects of their nature. We propose specific expressions to examine entropy related aspects of tests and estimate the values of entropy, emergence, self-organization, and complexity based on specific diversity and message length. © 2014 Wiley Periodicals, Inc. Complexity 20: 25-48, 2015
Year
DOI
Venue
2013
10.1002/cplx.21529
Complexity
Keywords
Field
DocType
self organization,information,complexity,artificial language,power law,computer code,entropy,natural language,emergence
Expression (mathematics),Sparse language,Source code,Computer science,Self-organization,Theoretical computer science,Software,Natural language processing,Message length,Artificial intelligence,Natural language,Constructed language,Machine learning
Journal
Volume
Issue
ISSN
abs/1311.5427
6
Complexity 20 6 429- (2015)
Citations 
PageRank 
References 
11
0.85
12
Authors
3
Name
Order
Citations
PageRank
Gerardo Febres1194.25
Klaus Jaffe2153.76
Carlos Gershenson339242.34