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Abstract

Interpreting quality is often discussed in relation to users’ perceptions, yet most user-oriented evidence is derived from surveys or experiments that only partially capture the way evaluation unfolds under broadcast and platform conditions. This article examines the real-time reception of simultaneous interpreting in a digitally mediated public event, focusing on a remote audience. Their unsolicited evaluative discourse is produced in a livestream chat rather than in co-present interactions. The dataset comprises 1,405 interpreting-related posts drawn from the YouTube livestream chat accompanying TVBS News’s broadcast of Jensen Huang’s COMPUTEX Taipei keynote address (2 June 2024), viewed by more than 50,000 concurrent users during the livestream. The analysis uses a multi-layered coding framework that combines sentiment polarity, Appraisal Theory and categories for non-evaluative discourse. It maps distributional patterns over time and derives recurrent theme clusters. The results show that audience reception is dominated by competence-oriented praise. Viewers also collectively monitored the interpreting setup, such as handovers and technical features. A substantial share of the posts engaged in speculation about agency, attributing the output to artificial intelligence. This speculation often precedes substantive quality criteria. These patterns highlight how platform-specific features and reduced status and authority cues shape the pragmatics of evaluation, which intensifies both criticism and appreciation. The study extends user-oriented quality research by theorizing platform-mediated SI reception as a socially negotiated process. Within this framework, quality judgements emerge from the public negotiation of access channels (e.g., source vs interpreted streams), identity attribution (human vs machine) and participation norms.

© John Benjamins Publishing Company
Available under the CC BY 4.0 license.
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2026-07-31
2026-08-16

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References

  1. Arzık-Erzurumlu, Ö. & Yılmaz, G.
    (2023) From remote control to tweets: How viewers’ use of Twitter shapes quality criteria in interpreting the Oscars. Interpreting (), –. 10.1075/intp.00083.arz
     https://doi.org/10.1075/intp.00083.arz [Google Scholar]
  2. Bühler, H.
    (1986) Linguistic (semantic) and extra-linguistic (pragmatic) criteria for the evaluation of conference interpretation and interpreters. Multilingua (), –. 10.1515/mult.1986.5.4.231
     https://doi.org/10.1515/mult.1986.5.4.231 [Google Scholar]
  3. Calvo-Ferrer, J. R.
    (2024) Can you tell the difference? A study of human vs machine-translated subtitles. Perspectives (), –. 10.1080/0907676X.2023.2268149
     https://doi.org/10.1080/0907676X.2023.2268149 [Google Scholar]
  4. Cheung, A. K. F.
    (2003) Does accent matter? The impact of accent in simultaneous interpretation into Mandarin and Cantonese on perceived performance quality and listener satisfaction level. InA. Collados Aís, M. M. Fernández Sánchez, & D. Gile (Eds.), La evaluación de la calidad en interpretación: Investigación. Granada: Comares, –.
     [Google Scholar]
  5. (2020) Interpreters’ perceived characteristics and perception of quality in interpreting. Interpreting (), –. 10.1075/intp.00033.che
     https://doi.org/10.1075/intp.00033.che [Google Scholar]
  6. Chiaro, D. & Nocella, G.
    (2004) Users’ quality expectations in conference interpreting: A survey through the World Wide Web. Meta (), –. 10.7202/009351ar
     https://doi.org/10.7202/009351ar [Google Scholar]
  7. Collados Aís, Á.
    (1998/2002) Quality assessment in simultaneous interpreting: The importance of nonverbal communication. InF. Pöchhacker & M. Shlesinger (Eds.), The interpreting studies reader. London: Routledge, –.
     [Google Scholar]
  8. Diriker, E.
    (2011) User expectation surveys: Questioning findings and drawing lessons for interpreter training. IU Journal of Translation Studies ().
     [Google Scholar]
  9. Dragos, V., Battistelli, D. & Kelodjoue, E.
    (2018) Beyond sentiments and opinions: Exploring social media with appraisal categories. In2018 21st International Conference on Information Fusion (FUSION), –. IEEE. 10.23919/ICIF.2018.8455751
     https://doi.org/10.23919/ICIF.2018.8455751 [Google Scholar]
  10. Franzke, A. S., Bechmann, A., Zimmer, M., Ess, C. & the Association of Internet Researchers
    (2019) Internet research: Ethical guidelines 3.0. https://aoir.org/reports/ethics3.pdf
     [Google Scholar]
  11. Guo, W., Guo, X., Huang, J. & Tian, S.
    (2024) Modeling listeners’ perceptions of quality in consecutive interpreting: A case study of a technology interpreting event. Humanities and Social Sciences Communications, . 10.1057/s41599‑024‑03511‑6
     https://doi.org/10.1057/s41599-024-03511-6 [Google Scholar]
  12. Krippendorff, K.
    (2018) Content analysis: An introduction to its methodology (4th ed.). SAGE Publications.
     [Google Scholar]
  13. Kurz, I.
    (1993) Conference interpreting: Expectations of different user groups. The Interpreters’ Newsletter, –.
     [Google Scholar]
  14. (2001) Conference interpreting: Quality in the ears of the user. Meta (), –. 10.7202/003364ar
     https://doi.org/10.7202/003364ar [Google Scholar]
  15. Kurz, I. & Pöchhacker, F.
    (1995) Quality in TV interpreting. Translatio: Nouvelles de la FIT — FIT Newsletter (), –.
     [Google Scholar]
  16. Liebeskind, C., Liebeskind, S. & Yechezkely, S.
    (2021) An analysis of interaction and engagement in YouTube live streaming chat. In2021 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/IOP/SCI), –. IEEE. 10.1109/SWC50871.2021.00045
     https://doi.org/10.1109/SWC50871.2021.00045 [Google Scholar]
  17. Madden, A., Ruthven, I. & McMenemy, D.
    (2013) A classification scheme for content analyses of YouTube video comments. Journal of Documentation (), –. 10.1108/JD‑06‑2012‑0078
     https://doi.org/10.1108/JD-06-2012-0078 [Google Scholar]
  18. Martin, J. R. & White, P. R. R.
    (2005) The language of evaluation: Appraisal in English. Basingstoke: Palgrave Macmillan. 10.1057/9780230511910
     https://doi.org/10.1057/9780230511910 [Google Scholar]
  19. Mohammad, S. M. & Turney, P. D.
    (2013) Crowd-sourcing a word–emotion association lexicon. Computational Intelligence (), –. 10.1111/j.1467‑8640.2012.00460.x
     https://doi.org/10.1111/j.1467-8640.2012.00460.x [Google Scholar]
  20. Moser, B.
    (1996) Quality in interpreting: Some methodological issues. The Interpreters’ Newsletter, –.
     [Google Scholar]
  21. Neuendorf, K. A.
    (2017) The content analysis guidebook (2nd ed.). SAGE Publications.
     [Google Scholar]
  22. Pang, B. & Lee, L.
    (2008) Opinion mining and sentiment analysis. Foundations and Trends in Information Retrieval (), –. 10.1561/1500000011
     https://doi.org/10.1561/1500000011 [Google Scholar]
  23. Pöchhacker, F.
    (2018) Media interpreting: From user expectations to audience comprehension. InE. Di Giovanni & Y. Gambier (Eds.), Reception studies and audiovisual translation. Amsterdam: John Benjamins, –. 10.1075/btl.141.13poc
     https://doi.org/10.1075/btl.141.13poc [Google Scholar]
  24. Recktenwald, J.
    (2017) Toward a transcription and analysis of live streaming on Twitch. Proceedings of the International Conference on Live Interfaces (ICLI 2017), –. 10.1016/j.pragma.2017.01.013
     https://doi.org/10.1016/j.pragma.2017.01.013 [Google Scholar]
  25. Ross, A., Corley, M. & Lai, C.
    (2024) Is there an uncanny valley for speech? Investigating listeners’ evaluations of realistic synthesised voices. Speech Prosody, –. 10.21437/SpeechProsody.2024‑225
     https://doi.org/10.21437/SpeechProsody.2024-225 [Google Scholar]
  26. Russo, M.
    (2005) Simultaneous film interpreting and users’ feedback. Interpreting (), –. 10.1075/intp.7.1.02rus
     https://doi.org/10.1075/intp.7.1.02rus [Google Scholar]
  27. Schierl, F.
    (2023) Reception of machine-translated and human-translated subtitles: A case study. InProceedings of the Machine Translation Summit XIX, Vol. 2: Users Track, –. https://aclanthology.org/2023.mtsummit-users.4/
     [Google Scholar]
  28. Suler, J.
    (2004) The online disinhibition effect. CyberPsychology & Behavior (), –. 10.1089/1094931041291295
     https://doi.org/10.1089/1094931041291295 [Google Scholar]
  29. (2005) The online disinhibition effect. Applied Psychoanalytic Studies (), –. 10.1002/aps.42
     https://doi.org/10.1002/aps.42 [Google Scholar]
  30. TVBS NEWS
    TVBS NEWS (2024, June2). [中文口譯] 6/2 LIVE 19:00 黃仁勳主題演講全程直播！NVIDIA CEO Jensen Huang’s keynote — AI人工智慧時代如何帶動全球新產業革命發展 COMPUTEX2024 [Chinese interpretation: Full livestream of NVIDIA CEO Jensen Huang’s keynote — How AI drives a new global industrial revolution, COMPUTEX 2024] [Video]. YouTube. https://www.youtube.com/watch?v=lp2xDN1HcwM
     [Google Scholar]
  31. Vuorikoski, A.
    (1998) User responses to simultaneous interpreting. InL. Bowker, M. Cronin, D. Kenny & J. Pearson (Eds.), Unity in diversity? Current trends in translation studies. Manchester: St. Jerome Publishing, –.
     [Google Scholar]
  32. Wehrmeyer, E.
    (2015) Comprehension of television news signed language interpreters: A South African perspective. Interpreting (), –. 10.1075/intp.17.2.03weh
     https://doi.org/10.1075/intp.17.2.03weh [Google Scholar]
  33. Yang, Y.
    (2023) “Feel sorry for Miss translator!!!”: A danmu-based case study of Bilibili users’ parasocial interactions about the ad hoc interpreter on screen. Interpreting (), –. 10.1075/intp.00086.yan
     https://doi.org/10.1075/intp.00086.yan [Google Scholar]
/content/journals/10.1075/intp.00136.fan
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Audience feedback on platform-mediated simultaneous interpreting in a livestream chat
John Benjamins ; https://doi.org/10.1075/intp.00136.fan
/content/journals/10.1075/intp.00136.fan
/content/journals/10.1075/intp.00136.fan
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  • Article Type: Research Article
Keywords: artificial intelligence ; audience reception ; interpreting quality ; platform-mediated interpreting

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