JOURNAL ARTICLE

Fan translation and affective mediation: A study of Hiddles' Translation Army of China.

  • Published In: Translation & Interpreting Studies: The Journal of the American Translation & Interpreting Studies Association, 2023, v. 18, n. 2. P. 261 1 of 3

  • Database: Communication Source 2 of 3

  • Authored By: Mo, Junru; Jin, Haina 3 of 3

Abstract

This study seeks to foreground the concept of 'affective mediation,' which is defined as an interventionist process in translation wherein affect is matched, managed, and modulated between communicating bodies. Situated in the context of fan translation, this study utilizes a multimodal analysis of the subtitling practice of Hiddles' Translation Army of China, a Chinese internet-based, celebrity-oriented fan translation group, and identifies three ways its fansubbers mediate affect toward the object of fandom, i.e., British actor, Tom Hiddleston. The findings suggest that the fansubber's mediation is conducive to restructuring the affective configuration in the target text and creates a site for emotive performance in fansubbing. The study also argues that affect-mediated fansubbing opens a new space outside the diegetic zone for an imagined interaction and relationship between the entire fandom community and the object of fandom. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Translation & Interpreting Studies: The Journal of the American Translation & Interpreting Studies Association. 2023/05, Vol. 18, Issue 2, p261
  • Document Type:Article
  • Subject Area:Biography
  • Publication Date:2023
  • ISSN:1932-2798
  • DOI:10.1075/tis.23012.mo
  • Accession Number:174239559
  • Copyright Statement:Copyright of Translation & Interpreting Studies: The Journal of the American Translation & Interpreting Studies Association is the property of John Benjamins Publishing Co. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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