Wide-spectrum characterization of long-running political phenomena on social media: The brexit case

In this study, we propose a wide-spectrum analysis of long-running political events on social media, with reference to an interesting real-world international case: the so-called Brexit, the process through which the United Kingdom activated the option of leaving the European Union. In this study, we model the users participating in 33 months of Twitter debate, covering their behaviour and demographics. By using publicly shared tweets, we developed a stance classification model to evaluate the change of stance over time. We also extracted the key topics of the long-running debate, studying which political side have discussed them most and what is the general sentiment on each. We also revealed the participation of bot accounts, and we found that the higher the bot score, the more likely the account is in a pro-Leave position. We conclude our study with a temporal and comparative analysis of politicians' social media accounts