| Title |
ASL-LEX: A lexical database of American Sign Language
|
|---|---|
| Published in |
Behavior Research Methods, May 2016
|
| DOI | 10.3758/s13428-016-0742-0 |
| Pubmed ID | |
| Authors |
Naomi K. Caselli, Zed Sevcikova Sehyr, Ariel M. Cohen-Goldberg, Karen Emmorey |
| Abstract |
ASL-LEX is a lexical database that catalogues information about nearly 1,000 signs in American Sign Language (ASL). It includes the following information: subjective frequency ratings from 25-31 deaf signers, iconicity ratings from 21-37 hearing non-signers, videoclip duration, sign length (onset and offset), grammatical class, and whether the sign is initialized, a fingerspelled loan sign, or a compound. Information about English translations is available for a subset of signs (e.g., alternate translations, translation consistency). In addition, phonological properties (sign type, selected fingers, flexion, major and minor location, and movement) were coded and used to generate sub-lexical frequency and neighborhood density estimates. ASL-LEX is intended for use by researchers, educators, and students who are interested in the properties of the ASL lexicon. An interactive website where the database can be browsed and downloaded is available at http://asl-lex.org . |
X Demographics
The data shown below were collected from the profiles of 35 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 7 | 20% |
| United Kingdom | 5 | 14% |
| Netherlands | 3 | 9% |
| Belgium | 1 | 3% |
| Italy | 1 | 3% |
| Germany | 1 | 3% |
| Unknown | 17 | 49% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 26 | 74% |
| Scientists | 7 | 20% |
| Science communicators (journalists, bloggers, editors) | 2 | 6% |
Mendeley readers
The data shown below were compiled from readership statistics for 82 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 1 | 1% |
| United States | 1 | 1% |
| Unknown | 80 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 28 | 34% |
| Researcher | 11 | 13% |
| Student > Master | 10 | 12% |
| Student > Bachelor | 5 | 6% |
| Student > Doctoral Student | 4 | 5% |
| Other | 11 | 13% |
| Unknown | 13 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Linguistics | 16 | 20% |
| Psychology | 13 | 16% |
| Neuroscience | 9 | 11% |
| Computer Science | 6 | 7% |
| Engineering | 5 | 6% |
| Other | 11 | 13% |
| Unknown | 22 | 27% |
Attention Score in Context
This research output has an Altmetric Attention Score of 24. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 October 2017.
All research outputs
#1,584,678
of 25,373,627 outputs
Outputs from Behavior Research Methods
#146
of 2,525 outputs
Outputs of similar age
#28,081
of 349,757 outputs
Outputs of similar age from Behavior Research Methods
#2
of 28 outputs
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So far Altmetric has tracked 2,525 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.1. This one has done particularly well, scoring higher than 94% of its peers.
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We're also able to compare this research output to 28 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.