Title |
Visual Iconicity Across Sign Languages: Large-Scale Automated Video Analysis of Iconic Articulators and Locations
|
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Published in |
Frontiers in Psychology, May 2018
|
DOI | 10.3389/fpsyg.2018.00725 |
Pubmed ID | |
Authors |
Robert Östling, Carl Börstell, Servane Courtaux |
Abstract |
We use automatic processing of 120,000 sign videos in 31 different sign languages to show a cross-linguistic pattern for two types of iconic form-meaning relationships in the visual modality. First, we demonstrate that the degree of inherent plurality of concepts, based on individual ratings by non-signers, strongly correlates with the number of hands used in the sign forms encoding the same concepts across sign languages. Second, we show that certain concepts are iconically articulated around specific parts of the body, as predicted by the associational intuitions by non-signers. The implications of our results are both theoretical and methodological. With regard to theoretical implications, we corroborate previous research by demonstrating and quantifying, using a much larger material than previously available, the iconic nature of languages in the visual modality. As for the methodological implications, we show how automatic methods are, in fact, useful for performing large-scale analysis of sign language data, to a high level of accuracy, as indicated by our manual error analysis. |
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United States | 5 | 8% |
Netherlands | 5 | 8% |
Spain | 3 | 5% |
Canada | 3 | 5% |
Ireland | 2 | 3% |
Sweden | 2 | 3% |
Norway | 2 | 3% |
Italy | 2 | 3% |
Other | 7 | 11% |
Unknown | 24 | 38% |
Demographic breakdown
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Members of the public | 35 | 55% |
Scientists | 27 | 42% |
Science communicators (journalists, bloggers, editors) | 2 | 3% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 24 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Master | 7 | 29% |
Researcher | 3 | 13% |
Student > Bachelor | 2 | 8% |
Professor > Associate Professor | 2 | 8% |
Student > Ph. D. Student | 2 | 8% |
Other | 4 | 17% |
Unknown | 4 | 17% |
Readers by discipline | Count | As % |
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Social Sciences | 2 | 8% |
Arts and Humanities | 1 | 4% |
Computer Science | 1 | 4% |
Agricultural and Biological Sciences | 1 | 4% |
Other | 2 | 8% |
Unknown | 4 | 17% |