🙏: Emoji and Religion in the Twitter Discourses on the Notre Dame Cathedral Fire

The fire that destroyed a large part of the world-famous Notre Dame Cathedral in France in April 2019 shocked the world. A lively expression of thoughts and feelings during and after the fire arose on Twitter. In this article, we will analyze the discourses about the Notre Dame fire on Twitter, with...

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Bibliographic Details
Published in:Journal of religion, media and digital culture
Subtitles:[Emoji Betende Hände]: Emoji and Religion in the Twitter Discourses on the Notre Dame Cathedral Fire
Authors: Elwert, Frederik (Author) ; Evolvi, Giulia (Author) ; Neumaier, Anna 1982- (Author) ; Wildt, Kim de 1975- (Author)
Format: Electronic Article
Language:English
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Published: Brill 2022
In: Journal of religion, media and digital culture
Standardized Subjects / Keyword chains:B Notre-Dame (Paris) / Fire disaster / Reactionary politics / Twitter (Softwareplattform) / Discourse / Emoticon
RelBib Classification:AD Sociology of religion; religious policy
AE Psychology of religion
CH Christianity and Society
KBG France
TK Recent history
ZG Media studies; Digital media; Communication studies
Further subjects:B Church
B Religious architecture
B emoji
B Sacred Space
B Social media
B Notre Dame
B Twitter
B Internet
B cathedral
Online Access: Presumably Free Access
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Summary:The fire that destroyed a large part of the world-famous Notre Dame Cathedral in France in April 2019 shocked the world. A lively expression of thoughts and feelings during and after the fire arose on Twitter. In this article, we will analyze the discourses about the Notre Dame fire on Twitter, with a specific focus on emoji, focusing on the thoughts and feelings emoji express and how they convey the meanings religious buildings have for people. Based on a dataset of almost 2 million tweets collected in the week following the incident, this paper leverages a variety of computational and qualitative methods to explore the topic from different angles. Temporal analysis and topic modelling show the dynamics of emoji usage, which drastically changes after a few days from expressing sorrow to expressing skepticism. Semantic analysis using the word2vec model reveals the implicit meaning of potentially ambiguous emoji characters.
ISSN:2165-9214
Contains:Enthalten in: Journal of religion, media and digital culture
Persistent identifiers:DOI: 10.1163/21659214-bja10071