MTurk crowdsourcing: A viable method for rapid discovery of Arabic nicknames?

Workshop on Creating Speech and Language Data with Amazon's Mechanical Turk, Mturk 2010 at the 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2010 - Proceedings

Volumn , Issue , 2010, Pages 89-92

  Higgins, Chiara ^a   McGrath, Elizabeth ^b   Moretto, Lailla ^b  

^a GEORGE MASON UNIVERSITY   (United States)

^b MITRE CORPORATION   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

SEARCH ENGINES;

ADVERTISING EFFECTS; AMAZON'S MECHANICAL TURKS; ARAB COUNTRIES; GOOGLE+; HUMAN INTELLIGENCE; MECHANICAL TURKS; NAMED ENTITIES; WORKERS';

CROWDSOURCING;

EID: 84856147189     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (4)

1. Callison-Burch, C. (2009). Fast, Cheap, and Creative: Evaluating Translation Quality Using Amazon's Mechanical Turk. Proceedings of the EMNLP. Singapore.
2. Halpern, J. (2009). Lexicon-Driven Approach to the Recognition of Arabic Named Entities. Second International Conference on Arabic Language Resources and Tools. Cairo.
3. Ross, J., Zaldivar, A., Irani, L., & Tomlinson, B. (2009). Who are the Turkers? Worker Demographics in Amazon. Department of Informatics, University of California, Irvine.
4. Snow, R., Jurafsy, D., & O'Connor, B. (2008). Cheap and fast - but is it good?: Evaluating Non-Expert Annotations for Natural Language Tasks. Proceedings of the 2008 Conference on Empirical Methods in Natural Language Processing, (pp. 254-263). Honolulu.