Investigation of Zipf&amp;#x2019;s &amp;#x2018;law-of-meaning&amp;#x2019; on Turkish corpora

Asso for Info Science & Tech

Vitevitch

2018

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.

Section: Introductionmentioning

confidence: 87%

μ \propto f^{δ},

where δ is a constant such that

δ \approx 1 / 2

. Equation defines Zipf's meaning‐frequency law.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The origins of Zipf's meaning‐frequency law

Asso for Info Science & Tech

Vitevitch

2018

“…As for the connection with laws of human language, we have found that more frequent whistle types tend to be associated to more behavioral contexts (in almost all the cases where the correlation test was possible), a feature that is reminiscent of a law of word meaning stating, as a tendency, that the higher the frequency of a word, the higher its number of meanings [4,12,13]. The finding of an inverse relationship between frequency and number of "meanings" or number of behavioral contexts is expected from information theory.…”

Section: Discussionmentioning

confidence: 99%

“…the tendency of more frequent words to have more meanings [12], has any parallel in dolphin whistle types. Quantitative linguistics studies on different languages have clearly shown that number of dictionary meanings of a word and its frequency are positively correlated [4,12,13].…”

Section: Introductionmentioning

confidence: 99%

A Law of Word Meaning in Dolphin Whistle Types

McCowan

2009

Entropy

Abstract:We show that dolphin whistle types tend to be used in specific behavioral contexts, which is consistent with the hypothesis that dolphin whistle have some sort of "meaning". Besides, in some cases, it can be shown that the behavioral context in which a whistle tends to occur or not occur is shared by different individuals, which is consistent with the hypothesis that dolphins are communicating through whistles. Furthermore, we show that the number of behavioral contexts significantly associated with a certain whistle type tends to grow with the frequency of the whistle type, a pattern that is reminiscent of a law of word meanings stating, as a tendency, that the higher the frequency of a word, the higher its number of meanings. Our findings indicate that the presence of Zipf"s law in dolphin whistle types cannot be explained with enough detail by a simplistic die rolling experiment.

Optimization Models of Natural Communication

Journal of Quantitative Linguistics

2017

A family of information theoretic models of communication was introduced more than a decade ago to explain the origins of Zipf's law for word frequencies. The family is a based on a combination of two information theoretic principles: maximization of mutual information between forms and meanings and minimization of form entropy. The family also sheds light on the origins of three other patterns: the principle of contrast, a related vocabulary learning bias and the meaning-frequency law. Here two important components of the family, namely the information theoretic principles and the energy function that combines them linearly, are reviewed from the perspective of psycholinguistics, language learning, information theory and synergetic linguistics. The minimization of this linear function is linked to the problem of compression of standard information theory and might be tuned by self-organization.