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      Languages Support Efficient Communication about the Environment: Words for Snow Revisited

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      1 , * , 2 , 3
      PLoS ONE
      Public Library of Science

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          Abstract

          The claim that Eskimo languages have words for different types of snow is well-known among the public, but has been greatly exaggerated through popularization and is therefore viewed with skepticism by many scholars of language. Despite the prominence of this claim, to our knowledge the line of reasoning behind it has not been tested broadly across languages. Here, we note that this reasoning is a special case of the more general view that language is shaped by the need for efficient communication, and we empirically test a variant of it against multiple sources of data, including library reference works, Twitter, and large digital collections of linguistic and meteorological data. Consistent with the hypothesis of efficient communication, we find that languages that use the same linguistic form for snow and ice tend to be spoken in warmer climates, and that this association appears to be mediated by lower communicative need to talk about snow and ice. Our results confirm that variation in semantic categories across languages may be traceable in part to local communicative needs. They suggest moreover that despite its awkward history, the topic of “words for snow” may play a useful role as an accessible instance of the principle that language supports efficient communication.

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          Compression and communication in the cultural evolution of linguistic structure.

          Language exhibits striking systematic structure. Words are composed of combinations of reusable sounds, and those words in turn are combined to form complex sentences. These properties make language unique among natural communication systems and enable our species to convey an open-ended set of messages. We provide a cultural evolutionary account of the origins of this structure. We show, using simulations of rational learners and laboratory experiments, that structure arises from a trade-off between pressures for compressibility (imposed during learning) and expressivity (imposed during communication). We further demonstrate that the relative strength of these two pressures can be varied in different social contexts, leading to novel predictions about the emergence of structured behaviour in the wild.
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            Efficiency and Complexity in Grammars

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              Kinship categories across languages reflect general communicative principles.

              Languages vary in their systems of kinship categories, but the scope of possible variation appears to be constrained. Previous accounts of kin classification have often emphasized constraints that are specific to the domain of kinship and are not derived from general principles. Here, we propose an account that is founded on two domain-general principles: Good systems of categories are simple, and they enable informative communication. We show computationally that kin classification systems in the world's languages achieve a near-optimal trade-off between these two competing principles. We also show that our account explains several specific constraints on kin classification proposed previously. Because the principles of simplicity and informativeness are also relevant to other semantic domains, the trade-off between them may provide a domain-general foundation for variation in category systems across languages.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                2016
                13 April 2016
                : 11
                : 4
                : e0151138
                Affiliations
                [1 ]Department of Linguistics, Cognitive Science Program, University of California, Berkeley, CA 94720, United States of America
                [2 ]Department of Psychology, University of California, Berkeley, CA 94720, United States of America
                [3 ]Department of Psychology, Carnegie Mellon University, Pittsburgh, PA 15213, United States of America
                Plymouth University, UNITED KINGDOM
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: TR CK. Performed the experiments: AC CK. Analyzed the data: CK. Wrote the paper: TR AC CK. Jointly led the project: TR CK.

                Article
                PONE-D-15-35167
                10.1371/journal.pone.0151138
                4830456
                27073981
                d153fa5b-c87f-4969-9a03-be69344f8776
                © 2016 Regier et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 22 August 2015
                : 22 February 2016
                Page count
                Figures: 7, Tables: 0, Pages: 17
                Funding
                This research was supported by the National Science Foundation ( www.nsf.gov) under grants SBE-1041707 (TR) and DGE-1106400 (AC). Publication was made possible in part by support from the Berkeley Research Impact Initiative (BRII) sponsored by the UC Berkeley Library.
                Categories
                Research Article
                Social Sciences
                Linguistics
                Languages
                Social Sciences
                Linguistics
                Social Sciences
                Sociology
                Communications
                Social Communication
                Social Media
                Twitter
                Computer and Information Sciences
                Network Analysis
                Social Networks
                Social Media
                Twitter
                Social Sciences
                Sociology
                Social Networks
                Social Media
                Twitter
                Social Sciences
                Linguistics
                Languages
                Language Families
                Social Sciences
                Linguistics
                Semantics
                Social Sciences
                Sociology
                Communications
                Earth Sciences
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                Geographic Areas
                Urban Areas
                Biology and Life Sciences
                Behavior
                Verbal Behavior
                Verbal Communication
                Custom metadata
                All relevant data are available either (1) within the paper and its Supporting Information files, or (2) at URLs supplied within the paper. However, access restrictions apply to some of the underlying data. Specifically, the Twitter data in this paper were acquired from Twitter’s streaming API, and redistribution of the text is prohibited by their terms of service (TOS). A complete set of word frequencies derived from that raw text for the purpose of the analyses in this paper is provided at https://github.com/cskemp/icesnow. The use of Twitter data in this paper is consistent with Twitter’s terms of service (TOS).

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