Crowdsourcing Translation

An Experience of a Cloud-based Messaging App


  • Razieh Azari University of Geneva
  • Marziyeh Khalilizadeh Ganjalikhani Higher Education Complex of Bam
  • Anahita Amirshoja’i Higher Education Complex of Bam


crowdsourcing translation, crowdsourcing translation platform, social media, Telegram


Crowdsourcing Translation (CT) platforms are constantly changing and developing in a dynamic and user-friendly approach. The rapid changes in technology have also accelerated this process. The present study focused on a new platform; a free cloud-based mobile and desktop messaging app called Telegram. Telegram’s technical features were discussed in the study. Then, experience of Iranian Translation Studies channel in using the app as CT platform and its implemented CT workflow were illustrated in details. It was shown that this general platform which has not been designed for crowdsourcing and CT specifically has essential features to be used as CT platform and has already been used as CT platform. Moreover, this app can be considered as a serious potential platform for CT especially in restricted situations.

Author Biographies

Razieh Azari, University of Geneva

Ph.D. Student in Translation Studies, Faculty of Translation and Interpreting

Marziyeh Khalilizadeh Ganjalikhani, Higher Education Complex of Bam

M.A. in Translation Studies, Faculty Member of the Higher Education Complex of Bam; PhD Student in Translation Studies, University of Isfahan, Isfahan, Iran


Anahita Amirshoja’i, Higher Education Complex of Bam

M.A. in Translation Studies, Faculty Member of the Higher Education Complex of Bam, Bam, Iran; Ph.D. Candidate in Translation Studies, Allameh Tabataba’i University, Tehran, Iran


Azari, R., Bouillon, P., Gerlach, J., Spechbach, H., & Halimi, S. (2019). Using crowdsourcing to evaluate lay-friendliness of BabelDr. In S. Mikkonen (Ed.), Proceedings of conference on easy-to-read language research (KLAARA 2019) (p. 6). Helsinki, Finland.

Bots: An Introduction for Developers. (n.d.). Retrieved October 23, 2019, from

Durov, P. (2018, March 22). 200,000,000 monthly active users. Retrieved from

Estellés, E., Navarro-Giner, R., & González, F. (2015). Crowdsourcing fundamentals: Definition and typology. In F. J. Simon-Garrigos, I. Gil-Pechuan, & S. Estelles-Miguel (Eds.), Advances in crowdsourcing (pp. 33–48). Springer International Publishing. doi: 10.1007/978-3-319-18341-1_3

FAQs. (n.d.). Retrieved October 23, 2019, from

Focused privacy, discussion groups, seamless web bots and more. (2019, May 31). Retrieved October 22, 2019, from

Howe, J. (2006, June 1). The rise of crowdsourcing. Wired. Retrieved from

Jiménez-Crespo, M. A. (2017). Crowdsourcing and online collaborative translations: Expanding the limits of translation studies. Amsterdam / Philadelphia: John Benjamins

MTurk Tracker. (2019, October 23). Retrieved October 23, 2019, from

Sangati, F., Abramova, E., & Monti, J. (2018). DialettiBot: a Telegram bot for crowdsourcing recordings of Italian dialects. In E. Cabrio, A, Mazzei, & F. Tamburini (Eds.), Proceedings of the fifth Italian conference on computational linguistics (CLiC-it 2018) (pp. 342–347). Torino, Italy: Accademia University Press. doi:10.4000/books.aaccademia.3609

Shekastan-e record-e enteshār-e matāleb dar kānālhā-ye omumi-ye Farsi zabān-e Telegram [Breaking the record of publishing content on Telegram Persian public channels]. (2017, August 12). Retrieved from:

Telegram FAQ. (n.d.). Retrieved October 22, 2019, from

Teʿdād-e kārbarān-e Irāni-ye Telegram va payāmresānhā-ye dākheli čeqadr 'ast [Statistics on Iranian Telegram and domestic messaging apps users]. (2019, May 22). Retrieved from



How to Cite

Azari, R., Khalilizadeh Ganjalikhani, M., & Amirshoja’i, A. (2020). Crowdsourcing Translation: An Experience of a Cloud-based Messaging App. Translation Studies Quarterly, 17(68), 7-22. Retrieved from



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