Golden Dawn's Visual Diary: An Analysis of Content Shared by Greek Extremists on Youtube from 2012 to 2019

34 Pages Posted: 8 Jul 2021 Last revised: 22 Sep 2021

Date Written: September 22, 2021

Abstract

New media such as Facebook, YouTube and Twitter introduced the world to a new era of instant communication. During this era where online interactions can even replace offline actions, Golden Dawn was the first openly neo-Nazi party after World War II to win seats in the parliament of a European country. Mainstream media banned its leaders indefinitely after Ilias Kasidiaris physically attacked Liana Kanelli, a member of the Greek Communist Party, on live television in June 2012. After the ban, many scholars seem to believe that Golden Dawn mobilised its voters online. This approach played a significant role in spreading their messages on social media while trying to appeal to wider audiences. This study samples 108 YouTube videos shared by Golden Dawn and uses Critical Discourse Analysis (CDA) to investigate the party’s activity on YouTube from 2012 to 2019. Official channels and politicians’ personal profiles are analyzed to explore their key messaging and style. Results of my analysis show that Golden Dawn’s messaging is populist, nationalist, extremist, and often adopts negative and emotional language. Additionally, their content openly promotes xenophobia and violence, and aims at causing insurrection by mobilizing supporters or in some cases calls for the executions of political opponents.

Keywords: Golden Dawn, extremism, nationalism, online key messaging, Greek politics, social media.

Suggested Citation

Samaras, Georgios, Golden Dawn's Visual Diary: An Analysis of Content Shared by Greek Extremists on Youtube from 2012 to 2019 (September 22, 2021). Available at SSRN: https://ssrn.com/abstract=3873562

Georgios Samaras (Contact Author)

King's College London ( email )

United Kingdom

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
3
Abstract Views
153
PlumX Metrics