The origins of Zipf's meaning‐frequency law
Ramon Ferrer‐i‐Cancho and
Michael S. Vitevitch
Journal of the Association for Information Science & Technology, 2018, vol. 69, issue 11, 1369-1379
Abstract:
In his pioneering research, G.K. Zipf observed that more frequent words tend to have more meanings, and showed that the number of meanings of a word grows as the square root of its frequency. He derived this relationship from two assumptions: that words follow Zipf's law for word frequencies (a power law dependency between frequency and rank) and Zipf's law of meaning distribution (a power law dependency between number of meanings and rank). Here we show that a single assumption on the joint probability of a word and a meaning suffices to infer Zipf's meaning‐frequency law or relaxed versions. Interestingly, this assumption can be justified as the outcome of a biased random walk in the process of mental exploration.
Date: 2018
References: Add references at CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
https://doi.org/10.1002/asi.24057
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:bla:jinfst:v:69:y:2018:i:11:p:1369-1379
Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=2330-1635
Access Statistics for this article
More articles in Journal of the Association for Information Science & Technology from Association for Information Science & Technology
Bibliographic data for series maintained by Wiley Content Delivery ().