Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Jacqueline Hoang Nguyen
University of Arts, Crafts and Design, Department of Fine Art. (KTD)
2019 (English)Conference paper, Oral presentation only (Other academic)
Abstract [en]

This panel discussion examines how images of conflict have shaped perceptions of Vietnam

Don McCullin’s photographs of the Vietnam War - known as the American War in Vietnam - have greatly influenced memories of the conflict, especially in the West. This panel discussion considers how notions of Vietnam have been shaped by images of conflict, and the wider cultural and historical narratives that have been neglected. Contributors include artists Sung Tieu and Jacqueline Hoàng Nguyễn, and art historian Mignon Nixon. The discussion is chaired by Richard Martin, Curator of Public Programmes, Tate.

Place, publisher, year, edition, pages
London, 2019.
Keywords [en]
Photography, Vietnam
National Category
Visual Arts
Research subject
Forskningsområden, Narrativa processer
Identifiers
URN: urn:nbn:se:konstfack:diva-7084OAI: oai:DiVA.org:konstfack-7084DiVA, id: diva2:1374378
Conference
VIETNAM: IMAGES OF A NATION
Available from: 2019-11-29 Created: 2019-11-29 Last updated: 2019-11-29

Open Access in DiVA

No full text in DiVA

By organisation
Department of Fine Art
Visual Arts

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 2 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf