Language in the age of dataism

Špela Vintar

doi:10.4312/slo2.0.2019.1.126-143

Avtorji

Špela Vintar University of Ljubljana

DOI:

https://doi.org/10.4312/slo2.0.2019.1.126-143

Ključne besede:

digitalizacija, jezikovne spremembe, digitalno jezikoslovje, jezikovna industrija

Povzetek

Digitalizacija vnaša korenite spremembe v jezik in komunikacijo, saj vpliva na načine izražanja, sredstva komunikacije in poti, prek katerih se širijo nove ideje. Obenem živimo v času, ko se naše jezikovno vedenje, naša sporočila in znanje skrbno beležijo, ti podatki pa se uporabljajo in prodajajo za urjenje pametnih tehnologij. V prispevku skušamo zaobjeti dinamiko teh sprememb s širše perspektive, in sicer se najprej osredotočimo na vpliv digitalizacije na sam jezik, nato analiziramo sodobne težnje v jezikovni industriji, kjer opažamo, da mnoge tradicionalne jezikovne storitve nadomeščajo tehnološko podprte in na podatkih temelječe rešitve, nazadnje pa obravnavamo vpliv tehnologij na človeka in družbo kot celoto. Iz širšega okvirja razprave izpeljemo utemeljitev in opredelitev področja digitalnega jezikoslovja kot interdisciplinarne vede, ki se z jezikom v digitalni dobi ukvarja s humanistično-družboslovnega izhodišča in vanj vključuje jezikoslovne, tehnološke, družbenoekonomske, infrastrukturne, kognitivne, etične in pravne vidike.

Prenosi

Podatki o prenosih še niso na voljo.

Literatura

Androutsopoulos, J. (2011). Language change and digital media: a review of conceptions and evidence. In N. Coupland & T. Kristiansen (Eds.), Standard languages and language standards in a changing Europe (pp. 145–161). Oslo: Novus Press.

Baker, M. (1993). Corpus linguistics and translation studies: Implications and applications. In M. Baker, G. Francis & E. Tognini-Bonelli (Eds.), Text and technology: In honour of John Sinclair (pp. 233–250). Amsterdam: John Benjamins.

Baron, Naomi S. (2008). Always on: Language in an Online and Mobile World. Oxford: Oxford University Press.

Building Trust in Human Centric Artificial Intelligence. EC COM(2019) 168. European Commission, 8. 4. 2019.

Bentivogli, L., Bisazza, A., Cettolo, M., & Federico, M. (2016). Neural versus phrase-based machine translation quality: a case study. In Proceedings of EMNLP 2016.

Bostrom, N. & Yudkowsky, E. (2014). The ethics of artificial intelligence. In W. Ramsey & K. Frankish (Eds.), The Cambridge handbook of artificial intelligence (pp. 316–334). Cambridge: Cambridge University Press.

Bowker, L. & Buitrago Ciro, J. (2015). Investigating the usefulness of machine translation for newcomers at the public library. Translation and Interpreting Studies, 10(2), 165–186.

Hamilton, W.L., Leskovec, J. & Jurafsky, D. (2016). Diachronic word embeddings reveal statistical laws of semantic change. In Proceedings of the Association for Computational Linguistics (ACL), Berlin.

Crystal, D. (2008). Txtng: The gr8 db8. Oxford: Oxford University Press.

Crystal, D. (2011). Internet Linguistics. London: Routledge.

Dürscheid, C., Wagner, F. & Brommer, S. (2010). Wie Jugendliche schreiben: Schreibkompetenz und neue Medien. Berlin & New York: de Gruyter.

Green, S., Heer, J. & Manning, C. D. (2013). The efficacy of human post-editing for language translation. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 439–448).

Goel, R., Soni, S., Goyal, N., Paparrizos, J., Wallach, H., Diaz, F. & Eisenstein, J. (2016). The social dynamics of language change in online networks. In International Conference on Social Informatics (pp. 41–57). Cham: Springer.

Guerberof, A. (2009). Productivity and quality in MT post-editing. In MT Summit XII-Workshop: Beyond Translation Memories: New Tools for Translators MT. August 29, 2009. Ottawa, ON, 8ff.

Harari, Y. N. (2015). Homo Deus: a Brief History of Tomorrow. London: Harvill Secker.

Johnson, M., Schuster, M., Quoc V. Le, Krikun, M., Wu, Y., Chen, Z. et al. (2017). Google’s multilingual neural machine translation system: Enabling zero-shot translation. Transactions of the Association for Computational Linguistics 5, 339–351.

Kenny, D. (2011). The ethics of machine translation. In Proceedings of the New Zealand Society of Translators and Interpreters Annual Conference 2011. Auckland, New Zealand.

Lenhart, A. (2008). Writing, technology, and teens. Washington, DC: Pew Internet and American Life Project. Retrieved from http://pewresearch.org/pubs/808/writing-technology-and-teens

[LIS 2016] 2016 Language Industry Survey – Expectations and Concerns of the European Language Industry. Retrieved from https://www.euatc.org/industry-surveys/item/download/5_57a02b9c45602ea9f7daf4440a7b2979

[LIS2017] 2017 Language Industry Survey – Expectations and Concerns of the European Language Industry. Retrieved from https://ec.europa.eu/info/sites/info/files/2017_language_industry_survey_report_en.pdf

[LIS2018] 2018 Language Industry Survey – Expectations and Concerns of the European Language Industry. Retrieved from

https://ec.europa.eu/info/sites/info/files/ 2018_language_industry_survey_report_en.pdf

Massardo, I.; van der Meer, J. (2017). The translation industry in 2022. TAUS BV, De Rijp, The Netherlands.

Massardo, I., van der Meer, J., Khalilov, M. (2016). TAUS Translation Technology Landscape Report. September 2016, TAUS BV, De Rijp, The Netherlands.

Mauranen, A., Kujamäki, P. (2004, Eds.). Translation universals: do they exist? Amsterdam: John Benjamins.

Melby, A. K., Warner, C. T. (1995). The possibility of language: a discussion of the nature of language, with implications for human and machine translation. Amsterdam & Philadelphia: John Benjamins Publishing.

Miličević, M., Ljubešić, N. & Fišer, D. (2017). Birds of a feather don’t quite tweet together. In D. Fišer & M. Beißwenger (Eds.), Investigating Computer-Mediated Communication: Corpus-Based Approaches to Language in the Digital World (pp. 14–43). Ljubljana: Faculty of Arts.

Moorkens, J., Lewis, D., Reijers, W., Vanmassenhove, E. & Way, A. (2016). Translation resources and translator disempowerment. In Tenth International Conference on Language Resources and Evaluation (LREC 2016), Portorož, Slovenia.

O’Brien, S. (2007). An Empirical Investigation of Temporal and Technical Post-Editing Effort. Translation and Interpreting Studies, 2(1), 83–136.

Pasquale, F. (2015) The black box society. Cambridge, MA: Harvard University Press.

Screen, B. (2019). What effect does post-editing have on the translation product from an end-user’s perspective?. Journal of specialised translation, 31, 133–157.

Smith, R. (2009). Copyright issues in translation memory ownership. ASLIB Translating and the Computer 31.

TAUS Keynotes Summer 2019. A Review of the TAUS Global Content Conference in Salt Lake City, UT (USA). TAUS Signature Editions, Amsterdam. Retrieved from www.taus.net

Toral, A. (2019). Post-editese: an exacerbated translationese. Proceedings of the Machine Translation Summit XVII Volume 1: Research track (pp. 273–281). Dublin, Ireland: EAMT.

Thurlow, C. (2007). Fabricating youth: new-media discourse and the technologization of young people. S. Johnson & A. Ensslin (Eds.), Language in the Media (pp. 213–233). London: Continuum.

Way A. (2018). Quality Expectations of Machine Translation. In J. Moorkens, S. Castilho, F. Gaspari, S. Doherty (Eds.), Translation Quality Assessment: From Principles to Practice (pp. 159–178). Cham: Springer. doi: https://doi.org/10.1007/978-3-319-91241-7_8

Zetzschke, J. (2019). (How) Do You Use MT? The Tool Box Journal, 19-11-306(2019). Retrieved from http://www.internationalwriters.com/toolkit/current.html#LETTER.BLOCK5