Journal
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
Volume 108, Issue 9, Pages 3526-3529Publisher
NATL ACAD SCIENCES
DOI: 10.1073/pnas.1012551108
Keywords
information theory; rational analysis
Categories
Funding
- National Science Foundation
- Social, Behavioral & Economic Sciences Doctoral Dissertation Research Improvement Grant
- National Science Foundation [0844472]
- Division Of Behavioral and Cognitive Sci
- Direct For Social, Behav & Economic Scie [1025309] Funding Source: National Science Foundation
- Division Of Behavioral and Cognitive Sci
- Direct For Social, Behav & Economic Scie [0844472] Funding Source: National Science Foundation
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We demonstrate a substantial improvement on one of the most celebrated empirical laws in the study of language, Zipf's 75-y-old theory that word length is primarily determined by frequency of use. In accord with rational theories of communication, we show across 10 languages that average information content is a much better predictor of word length than frequency. This indicates that human lexicons are efficiently structured for communication by taking into account interword statistical dependencies. Lexical systems result from an optimization of communicative pressures, coding meanings efficiently given the complex statistics of natural language use.
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