Affiliation:
1. Glasgow Caledonian University
2. Universitat de València
3. Universitat Politècnica de València
Abstract
The coronavirus disease Covid-19 (SARS-CoV-2) pandemic is exacting a huge toll on individuals, families, communities, and societies across the world. The study of public communication is a key aspect for slowing the spread of the virus and therefore reducing the death rate. This article analyses political leaders’ crisis communication during the Covid-19 pandemic of the most affected European countries, Boris Johnson (United Kingdom), Emmanuel Macron (France), Pedro Sánchez (Spain) and Giuseppe Conte (Italy), in addition to Tedros Adhanom as a representative of the World Health Organisation (WHO) and Ursula Von der Leyen President of the European Union (EU). The study focuses on the visual information (images and videos) published in their Twitter profiles, with the aim of highlighting the strategies of recommendations by health authorities during the first 40 days of the pandemic. After analysis of the visual content of 634 tweets, the results show significant differences amongst the preventative measures recommended (social distancing, use of masks, hand washing, etc.) and the public image projected by the leaders in their Twitter profiles.
Publisher
Ediciones Profesionales de la Informacion SL
Subject
Library and Information Sciences,Information Systems
Reference82 articles.
1. Agre, Philip E. (2002). “Real-time politics: The internet and the political process”. The information society, v. 18, n. 5, pp. 311-331. https://doi.org/10.1080/01972240290075174
2. Alhabash, Saleem; McAlister, Anna R. (2014). “Redefining virality in less broad strokes: Predicting viral behavioral intentions from motivations and uses of Facebook and Twitter”. New media & society, v. 17, n. 8, pp. 1317-1339. https://doi.org/10.1177/1461444814523726
3. Alonso-Muñoz, Laura; Casero-Ripollés, Andreu (2020). “Populism against Europe in social media: the Eurosceptic discourse on Twitter in Spain, Italy, France and United Kingdom during the campaign of the 2019 European Parliament Election”. Frontiers in communication, v. 5, n. 54. https://doi.org/10.3389/fcomm.2020.00054
4. Aramaki, Eiji; Maskawa, Sachiko; Morita, Mizuki (2011). “Twitter catches the flu: detecting influenza epidemics using Twitter”. In: Proceedings of the 2011 Conference on empirical methods in natural language processing, pp. 1568-1576. Association for Computational Linguistics. http://www.aclweb.org/anthology/D11-1145
5. Arora, Anuja; Bansal, Shivam; Kandpal, Chandrashekhar; Aswani, Reema; Dwivedi, Yogesh (2019). “Measuring social media influencer index-insights from Facebook, Twitter and Instagram”. Journal of retailing and consumer services, v. 49, pp. 86-101. https://doi.org/10.1016/j.jretconser.2019.03.012
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