On 23 June 2016, the United Kingdom held a referendum, whether the British people prefer to stay in the European Union or leave. In this referendum, the people voted 51.9% supporting leaving the EU. As a result, the Government invoked Article 50 of the Treaty on European Union, starting a two-year process which was due to conclude with the UK’s exit on 29 March 2019. This process is since referred to as “Brexit”, which is used as a shorthand way of saying the UK leaving the EU – merging the words Britain and exit to get Brexit.

In this project, we are going to study how the public’s views towards Brexit developed before, during and after the European Elections of 26 May 2019, an action that the British Parliament wanted to avoid, but had to attend, nevertheless. The public’s sentiment was studied through the views expressed on Twitter, a famous social network, where people are free to express their views in short sentences. For the prediction of the sentiment, the emotion and the geolocation of the public’s views, a set of machine learning algorithms were employed.