Internet Memes as Partial Stories: Identifying Political Narratives in Coronavirus Memes
Item
Title
Internet Memes as Partial Stories: Identifying Political Narratives in Coronavirus Memes
Social Media + Society
Creator
Constance de Saint Laurent
Vlad P. Glăveanu
Ioana Literat
Subject
COVID-19
Reddit
coronavirus
internet memes
narrative
narrative psychology
politics
social media
Abstract
This article advances a narrative approach to internet memes conceptualized as partial stories that reflect, capture, and contribute to wider storylines. One key difficulty in studying memes as stories rests in the fact that narrative analysis often focuses on plot at the expense of roles and characters. Building on narrative psychology and, in particular, transactional and linguistic types of analysis, we propose a typology of character roles—Persecutor, Victim, Hero, and Fool—that is useful to uncover scenarios within memes and, thus, reveal their intrinsic narrative structure. We apply this framework to the analysis of political narratives embedded within 241 coronavirus memes systematically sampled from Reddit’s r/CoronavirusMemes between January and May 2020. Five main scenarios or storylines emerged from this analysis, the first four depicting a more or less common narrative of protest against the incompetence and/or malevolence of the political class—from Donald Trump and the Republicans in the United States to Boris Johnson and the Conservatives in the United Kingdom and, finally, to politicians in Asia such as Xi Jinping and Kim Jong-un—while the fifth scenario brought to the fore social categories made salient by the pandemic and focused especially on the relation between people who respect and don’t respect measures. The psychological, social, and political implications of these scenarios in relation to the pandemic are discussed, as well as the broader consequences of studying memes as narrative structures.
volume
7
issue
1
pages
2056305121988932
Date
January 1, 2021
short title
Social Media + Society
Internet Memes as Partial Stories
Language
en
doi
10.1177/2056305121988932
issn
2056-3051