Tweeting the environment #Brexit / by Jingrong Tong, Landong Zuo.
Material type:
TextSeries: Emerald pointsPublication details: Bingley, UK : Emerald Publishing, 2018.Description: 1 online resource (215 p.)ISBN: - 9781787564992 (ebk)
- 9781787565012 (ebk)
- 320.941
| Item type | Current library | Call number | Status | Notes | Barcode | |
|---|---|---|---|---|---|---|
Electronic resources
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Marbella International University Centre | 320.941 TON twe (Browse shelf(Opens below)) | Available | E-book | EBC5530899 |
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| 320.941 FOR mas Mastering British politics / | 320.941 MOR pol Politics and governance in the UK | 320.941 POL pol Politics UK / | 320.941 TON twe Tweeting the environment #Brexit / | 320.941 WAT bri British government and politics : a comparative guide | 320.9410904 GRI bri British politics | 320.946 GUN dem Democracy in modern Spain / |
Ch. 1. Introduction --
Ch. 2. The Environment and Politics --
Ch. 3. Twitter, the Media Ecology and Environmental Communication --
Ch. 4. Environmental Discourses on Twitter --
Ch. 5. Elite Domination in the Asymmetrical Twitter Space --
Ch. 6. Sparse “Communities” and their Green Bridges in Twitter Networks --
Ch. 7. Influential Social Actors: Competing for Discourses on Twitter --
Ch. 8. Twitter and Environmental Politics --
Ch. 9. Social Media Research: Towards an Inductive Approach.
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.
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