This book explores Twitter communication about the 2016 Brexit referendum in the UK in the run-up to the event. The mixed-method, computational analysis of over twelve million tweets reveals how Twitter worked in shaping political discourse and its potential for fuelling populism in the month leading to the referendum. Our findings show while polarised public opinion was explicitly expressed, populist sentiments were mainstreamed into the debate about the referendum and widely spread on Twitter. Populist politicians, supported by pro-Brexit users, tactically used Twitter to promulgate their populist ideas. In contrast, despite their active use of Twitter, the Remain camp appeared to have misunderstood the mechanisms of Twitter for shaping political discourse. Twitter communication, in this case, showed dangerous potential for reflecting and reinforcing existing social tensions and divisions, being influenced or even manipulated by individuals and interest groups to serve their own interests. It is important to be well aware of this capacity of Twitter for the wellbeing of democracy, especially in the politically turbulent times since 2016 when the UK voted to leave the EU.

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.