Article published in:Fair MT: Towards ethical, sustainable Machine Translation
Edited by Joss Moorkens, Dorothy Kenny and Félix do Carmo
[Translation Spaces 9:1] 2020
► pp. 98–122
Machine translation in the news
A framing analysis of the written press
Machine translation (MT) is now firmly in the public eye. The media can reflect and influence the public perception of MT and, by extension, of translation itself, but the news coverage of MT has to date remained largely unexplored. This study draws on the news framing literature to present an analysis of how MT is described in the written press. Based on a sample of 284 MT-focused newspaper articles, the news reporting on MT was found to be significantly more positive than negative. This positive framing was unrelated to the launch of neural MT. Furthermore, the portrayal of MT in the press tended to lack nuance, with few instances that raised awareness of the technology’s use implications. The study calls for higher standards in the public discussion and promotion of MT and for more research on non-professional conceptualisations of translation technologies and their role in communication.
Keywords: machine translation, news coverage, news framing, content analysis, translation technology
- 2.Review of literature
- 3.2Content analysis
- 4.1Valenced frames: Quantitative analysis
- 4.2Positive articles
- 4.3Negative articles
- 4.4Neutral articles
Published online: 17 August 2020
Bahdanau, Dzmitry, Kyunghyun Cho, and Yoshua Bengio
2015 “Neural Machine Translation by Jointly Learning to Align and Translate.” Accessed 3 March 2020, https://arxiv.org/abs/1409.0473
2019 “Translation Errors Force Osaka Metro Websites Offline.” BBC News, March 19 2019 Accessed 28 October 2019, https://www.bbc.co.uk/news/world-asia-47622639
Bowker, Lynne, and Jairo Buitrago Ciro
Cadwell, Patrick, Sharon O’Brien, and Carlos S. C. Teixeira
de Vreese, Claes H.
de Vreese, Claes H., and Hajo Boomgaarden
Grissom, Robert J., and John J. Kim
Hassan, Hany, Anthony Aue, Chang Chen, Vishal Chowdhary, Jonathan Clark, Christian Federmann, Xuedong Huang, Marcin Junczys-Dowmunt, William Lewis, Mu Li, Shujie Liu, Tie-Yan Liu, Renqian Luo, Arul Menezes, Tao Qin, Frank Seide, Xu Tan, Fei Tian, Lijun Wu, Shuangzhi Wu, Yingce Xia, Dongdong Zhang, Zhirui Zhang, and Ming Zhou
2018 “Achieving Human Parity on Automatic Chinese to English News Translation.” Accessed 3 March 2020, https://arxiv.org/abs/1803.05567
2015 “Google Translate Error Sees Spanish Town Advertise Clitoris Festival.” The Guardian 3 November 2015 Accessed 28 October 2019, https://www.theguardian.com/world/2015/nov/03/google-translate-error-as-pontes-spain-clitoris-food-festival-grelo-galicia
Kockaert, Hendrik J.
Läubli, Samuel, and David Orrego-Carmona
Mokken, R. J.
Moorkens, Joss, and Sharon O’Brien
2015 “Post-Editing Evaluations: Trade-Offs Between Novice and Professional Participants.” In Proceedings of European Association for Machine Translation (EAMT) 2015, Antalya, edited by İlknur Durgar El-Kahlout, Mehmed Özkan, Felipe Sánchez-Martínez, Gema Ramírez-Sánchez, Fred Hollowood, and Andy Way, 75–81.
Neuman, Russell, Marion R. Just, and Ann N. Crigler
2018 “Machine Translation in Everyday Life: What Makes FAUT MT Workable?” TAUS eLearning Blogs 29 March 2019 Accessed 3 March 2020, https://blog.taus.net/elearning/machine-translation-in-everyday-life-what-makes-faut-mt-workable
2018 “Microsoft Announces Breakthrough in Chinese-to-English Machine Translation.” Tech Crunch. Accessed 5 September 2019, https://techcrunch.com/2018/03/14/microsoft-announces-breakthrough-in-chinese-to-english-machine-translation/?guccounter=1&guce_referrer_us=aHR0cHM6Ly93d3cuZ29vZ2xlLmNvbS8&guce_referrer_cs=9OFjK0HSW-I5Dw0bK1fsrw
Rossi, Caroline, and Jean-Pierre Chevrot
Schuck, Andreas R. T., and Claes H. de Vreese
Semetko, H. A., and P. M. Valkenburg
Stochl, Jan, Peter Jones, and Tim Croudace
2018 “Microsoft’s Chinese-English Translation System Achieves Human Parity.” Computer Weekly, Accessed 5 September 2019, https://www.computerweekly.com/news/252436868/Microsofts-Chinese-English-translation-system-achieves-human-parity
2020 Westlaw. Thomson Reuters, Accessed 26 June 2019. https://intl.westlaw.com/
Toral, Antonio, Sheila Castilho, Ke Hu, and Andy Way
Vieira, Lucas N., and Elisa Alonso
Vieira, Lucas N., Elisa Alonso, and Lindsay Bywood
Wu, Yonghui, Mike Schuster, Zhifeng Chen, Quoc V. Le, Mohammad Norouzi, Wolfgang Macherey, Maxim Krikun, Yuan Cao, Qin Gao, Klaus Macherey, Jeff Klingner, Apurva Shah, Melvin Johnson, Xiaobing Liu, Łukasz Kaiser, Stephan Gouws, Yoshikiyo Kato, Taku Kudo, Hideto Kazawa, Keith Stevens, George Kurian, Nishant Patil, Wei Wang, Cliff Young, Jason Smith, Jason Riesa, Alex Rudnick, Oriol Vinyals, Greg Corrado, Macduff Hughes, and Jeffrey Dean
2016 “Google’s Neural Machine Translation System: Bridging the Gap between Human and Machine Translation.” Accessed 3 March 2020, http://arxiv.org/abs/1609.08144
Cited by 1 other publications
Asscher, Omri & Ella Glikson
This list is based on CrossRef data as of 11 november 2021. Please note that it may not be complete. Sources presented here have been supplied by the respective publishers. Any errors therein should be reported to them.