Amazon Mechanical Turk: A Research Tool for Organizations and Information Systems Scholars

Author:

Crowston Kevin

Publisher

Springer Berlin Heidelberg

Reference24 articles.

1. Snow, R., O’Connor, B., Jurafsky, D., Ng, A.Y.: Cheap and fast—But is it good?: Evaluating non-expert annotations for natural language tasks. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing, pp. 254–263. Association for Computational Linguistics (2008)

2. Kaisser, M., Lowe, J.: Creating a research collection of question answer sentence pairs with Amazon’s Mechanical Turk. In: Proceedings of the Sixth International Conference on Language Resources and Evaluation, LREC 2008 (2008)

3. Rashtchian, C., Young, P., Hodosh, M., Hockenmaier, J.: Collecting image annotations using Amazon’s Mechanical Turk. In: Proceedings of the NAACL HLT 2010 Workshop on Creating Speech and Language Data with Amazon’s Mechanical Turk, pp. 139–147. Association for Computational Linguistics (2010)

4. Sorokin, A., Forsyth, D.: Utility data annotation with Amazon Mechanical Turk. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, pp. 1–8 (2008), doi:10.1109/CVPRW.2008.4562953

5. Heer, J., Bostock, M.: Crowdsourcing graphical perception: Using Mechanical Turk to assess visualization design. In: Proceedings of the 28th International Conference on Human Factors in Computing Systems (CHI 2010), pp. 203–212. ACM (2010), doi:10.1145/1753326.1753357

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