Projects per year
Abstract
Two language laws have been identified as consistent patterns shaping animal behaviour, both acting on the organizational level of communicative systems. Zipf's law of brevity describes a negative relationship between behavioural length and frequency. Menzerath's law defines a negative correlation between the number of behaviours in a sequence and average length of the behaviour composing it. Both laws have been linked with the information-theoretic principle of compression, which tends to minimize code length. We investigated their presence in a case study of male chimpanzee sexual solicitation gesture. We failed to find evidence supporting Zipf's law of brevity, but solicitation gestures followed Menzerath's law: longer sequences had shorter average gesture duration. Our results extend previous findings suggesting gesturing may be limited by individual energetic constraints. However, such patterns may only emerge in sufficiently large datasets. Chimpanzee gestural repertoires do not appear to manifest a consistent principle of compression previously described in many other close-range systems of communication. Importantly, the same signallers and signals were previously shown to adhere to these laws in subsets of the repertoire when used in play; highlighting that, in addition to selection on the signal repertoire, ape gestural expression appears shaped by factors in the immediate socio-ecological context.
Original language | English |
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Article number | 220849 |
Number of pages | 13 |
Journal | Royal Society Open Science |
Volume | 9 |
Issue number | 11 |
Early online date | 9 Nov 2022 |
DOIs | |
Publication status | Published - 9 Nov 2022 |
Keywords
- Compression
- Communication
- Zipf
- Menzerath
- Language
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- 1 Finished
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Cat Hobaiter: H2020 ERC Starting Grant 2018 GESTURALORIGINS
Hobaiter, C. (PI)
1/03/19 → 28/02/24
Project: Fellowship
Datasets
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Wild-Minds/LinguisticLaws_Papers: Variable expression of linguistic laws in ape gesture: a case study from chimpanzee sexual solicitation
ASafryghin (Creator) & Hobaiter, C. (Creator), Zenodo, 2022
Dataset