JOURNAL ARTICLE

The New Media Art world in Turkey: Boundary-work in action.

  • Published In: Convergence: The Journal of Research into New Media Technologies, 2025, v. 31, n. 1. P. 242 1 of 3

  • Database: Communication Source 2 of 3

  • Authored By: Yeğinsü, İpek 3 of 3

Abstract

This article examines the professional ideology of the New Media Art territory in Turkey through the lens of Thomas F. Gieryn's concept of boundary-work, based on semi-structured interviews with artists, curators, and producers. It finds that since the mid-1990s, Turkey's New Media Art scene has developed largely in parallel with global trends but is characterized by two main ideological variants correlated with career orientation: an academic variant emphasizing critical theory, activism, and interdisciplinarity, and a managerial variant focusing on technological innovation, audience experience, and commercial collaboration. Artists exhibit greater flexibility in navigating these variants due to diverse practices and the ability to engage with multiple professional territories, though funding limitations in Turkey influence their professional strategies. The study highlights ongoing tensions between maintaining critical artistic autonomy and engaging with corporate interests, suggesting that future developments in the field will depend significantly on local funding structures and institutional support.

Additional Information

  • Source:Convergence: The Journal of Research into New Media Technologies. 2025/02, Vol. 31, Issue 1, p242
  • Document Type:Article
  • Subject Area:Social Sciences and Humanities
  • Publication Date:2025
  • ISSN:1354-8565
  • DOI:10.1177/13548565241284533
  • Accession Number:183687341
  • Copyright Statement:Copyright of Convergence: The Journal of Research into New Media Technologies is the property of Sage Publications Inc. 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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