%0 Journal Article
%9 ACL : Articles dans des revues avec comité de lecture répertoriées par l'AERES
%A Morin, C.
%A Mercier, A.
%A Atlani Duault, Laëtitia
%T Text-image relationships in tweets : shaping the meanings of an epidemic
%D 2019
%L fdi:010075594
%G ENG
%J Societies
%@ 2075-4698
%K social media ; Twitter ; text-image relationships ; pragmatics ; health ; crisis
%M ISI:000464277100002
%N 1
%P art. 12 [18 ]
%R 10.3390/soc9010012
%U https://www.documentation.ird.fr/hor/fdi:010075594
%> https://horizon.documentation.ird.fr/exl-doc/pleins_textes/divers19-04/010075594.pdf
%V 9
%W Horizon (IRD)
%X 1. Background: While many studies analyze the functions that images can fulfill during humanitarian crises or catastrophes, an understanding of how meaning is constructed in text-image relationships is lacking. This article explores how discourses are produced using different types of text-image interactions. It presents a case study focusing on a humanitarian crisis, more specifically the sexual transmission of Ebola. 2. Methods: Data were processed both quantitatively and qualitatively through a keyword-based selection. Tweets containing an image were retrieved from a database of 210,600 tweets containing the words "Ebola" and "semen", in English and in French, over the course of 12 months. When this first selection was crossed with the imperative of focusing on a specific thematic (the sexual transmission of Ebola) and avoiding off-topic text-image relationships, it led to reducing the corpus to 182 tweets. 3. Results: The article proposes a four-category classification of text-image relationships. Theoretically, it provides original insights into how discourses are built in social media; it also highlights the semiotic significance of images in expressing an opinion or an emotion. 4. Conclusion: The results suggest that the process of signification needs to be rethought: Content enhancement and dialogism through images have a bearing on Twitter's use as a public sphere, such as credibilization of discourses or politicization of events. This opens the way to a new, more comprehensive approach to the rhetorics of users on Twitter.
%$ 056 ; 052 ; 124