SUBTLEX-AR: Arabic word distributional characteristics based on movie subtitles
This article presents SUBTLEX-AR, a digital database providing an extensive collection of attributes related to Modern Standard Arabic words (Arabic for short). SUBTLEX-AR combines a novel dataset of 120 million word tokens from movie subtitles with 40 million tokens from newspaper articles originally collected in ARALEX (Boudelaa & Marslen-Wilson, Behavior Research Methods, 42, 481-487, 2010), ensuring comprehensive coverage. SUBTLEX-AR provides information about the statistical properties of Arabic words at the orthographic, phonological, morphological, and semantic levels. The database also includes information on sub-word structure properties like bigram and trigram frequencies, as well as lemmas and part-of-speech information along with their corresponding frequencies. The online interface of SUBTLEX-AR allows users either to upload a set of words to receive their properties or to receive a set of words matching constraints on predefined properties. The properties themselves are easily extensible and will be expanded over time. SUBTLEX-AR is freely accessible here: https://subtlexar.uaeu.ac.ae/.
Authors
- Manuel Perea (ORCID: https://orcid.org/0000-0002-3291-1365)
- Manuel Carreiras (ORCID: https://orcid.org/0000-0001-6726-7613)
- Sami Boudelaa (ORCID: https://orcid.org/0000-0002-1870-7202)
- Nazrin Jariya
Institutions
- Ikerbasque (ES)
- Universitat de València (ES)
- University of the Basque Country (ES)
- United Arab Emirates University (AE)
- Universidad Nebrija (ES)
- Basque Center on Cognition, Brain and Language (ES)
Publication Details
- Journal
- Behavior Research Methods
- Published
- 2025-02-26
- DOI
- https://doi.org/10.3758/s13428-024-02560-8
- Citations
- 2
- Primary Topic
- Subtitles and Audiovisual Media
- Type
- article
- Field-Weighted Citation Impact
- 20.85
Funders
- United Arab Emirates University