The level of politicisation of the environment has been low in the UK. Economic concerns outweigh environmental ones in political debates, public policies and political agendas. Can the rise of social media communication change this situation?
Tweeting the Environment #Brexit argues that, although limited by the dynamics of the British context, the technological affordances of Twitter enabled social actors such as the Green Party, ENGOs, and their associates to advance their political and green claims in order to mobilise voters before the 2016 EU referendum and to express their concerns in order to change environmental politics in the aftermath.
The interdisciplinary research employed a combination of big data applications such as ElasticSearch and Kibana and desktop applications such as Gephi and SPSS in analysing large-scale social data. Adopting an inductive and data-driven approach, this book shows the importance of mixed methods and the necessity of narrowing down "big" to "small" data in large-scale social media research.
Rezensionen / Stimmen
Tong, a lecturer in digital media and culture in the UK, and Zuo, an information technology consultant and data scientist specializing in data mining, data analysis, and natural language processing, examine Twitter discourses and networks about environmental considerations in the discussions about the UK's 2016 referendum to leave the European Union and its aftermath. They consider how the discourse is constructed in tweets on the environmental aspects of the referendum; how users were connected to each other in this environmental communication; which social actors influenced the discourses and networks and how they did so; and what the discourses, networks, and roles played by social actors suggest about environmental politics on Twitter and in the UK. They draw on discourse and network analysis of about 112,000 related tweets collected in real time between May and July 2016, discussing the relationship between environmental issues and politics and between Brexit and the environment; the media landscape within which Twitter exists and key debates in the fields of Twitter communication and environmental communication on Twitter; environmental discourses in tweets and the nature of the environmental considerations in the discussion about the referendum on Twitter; elite domination on Twitter; social network analysis of the environmental data; the tweeting practices and discursive arguments of influential social actors; and insights from the study about social media and environmental politics and social media research and their methodological approach. The book originated from the authors' paper presented at the International Environmental Communication Association Annual Conference in 2017 in the UK. -- Annotation (c)2018 * (protoview.com) *
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ISBN-13
978-1-78756-501-2 (9781787565012)
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Schweitzer Klassifikation
Dr Jingrong Tong is Senior Lecturer in Digital Media and Culture at Brunel University London, UK. Her current research focuses on digital technology and journalism, social data analysis and environmental communication. She is the author of two books on investigative Journalism in China and the co-editor of an edited book on digital technology and journalism.Dr Landong Zuo is an IT Consultant and Data Scientist specialized in data mining, data analysis and Nature Language Processing, UK. His research interests include data integration, analysis and visualization in the fields of Semantic Web, Linked Data and Big Data.
Autor*in
Brunel University London, UK
IT Solution Architect, UK
Chapter 1. Introduction Chapter 2. The Environment and Politics
Chapter 3. Twitter, the Media Ecology and Environmental Communication
Chapter 4. Environmental Discourses on Twitter
Chapter 5. Elite Domination in the Asymmetrical Twitter Space
Chapter 6. Sparse "Communities" and their Green Bridges in Twitter Networks
Chapter 7. Influential Social Actors: Competing for Discourses on Twitter
Chapter 8. Twitter and Environmental Politics
Chapter 9. Social Media Research: Towards an Inductive Approach
