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            Visual Citizenship

            Communicating political opinions and emotions on social media

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            Author(s)
            Bouko, Catherine
            Language
            English
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            Abstract
            This book explores visual political engagement online – how citizens participate in the dynamism of life in society by expressing their opinions and emotions on various issues of democratic life in image-based social media posts, independently of collective actions. Looking beyond large digital social movements to focus on the everyday, the book provides a well-documented and comprehensive framework of key notions, concrete methods and examples of empirical insights into everyday visual citizenship on social media. It shows how the visual has become ubiquitous in citizens’ communication on social media, focusing on how citizens use visual content to express their emotions and opinions on social media platforms when they discuss politics in a large sense. With this book, every reader interested in political communication, visual communication and/or new media is fully equipped to analyse everyday visual citizenship on social media platforms. The Open Access version of this book, available at http://www.taylorfrancis.com, has been made available under a Creative Commons [Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND)] 4.0 license.
            URI
            https://doab-dev.siscern.org/handle/20.500.12854/180531
            Keywords
            citizenship;content;discourse;emotion;frame;opinion;politics;semiotics;social media;visual
            DOI
            10.4324/9781003398806
            ISBN
            9781032505060, 9781003398806, 9781032505053
            Publisher
            Taylor & Francis
            Publisher website
            http://www.taylorandfrancis.com/
            Publication date and place
            2024
            Imprint
            Routledge
            Series
            Routledge Studies in Media, Communication, and Politics,
            Pages
            348
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            Credits


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              This project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871069.

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