@inproceedings{47c5df5f6d504afeadb8c75b14b30869,
title = "BREXIT: A granger causality of twitter political polarisation on the FTSE 100 Index and the Pound",
abstract = "BREXIT is the single biggest geopolitical event in British history since WWII. Whilst the political fallout has become a tragicomedy, the political ramifications has had a profound impact on the Pound and the FTSE 100 index. This paper examines Twitter political discourse surrounding the BREXIT withdrawal agreement. In particular we focus on the discussions around four different exit strategies known as 'Norway', 'Article 50', the'Backstop' and 'No Deal' and their effect on the pound and FTSE 100 index from the period of rumblings of the cancellation of the Meaning Vote on December 10th 2018 inclusive of second defeat on the Prime Minister's BREXIT exit strategy on February 14th to February 24th 2019. Our approach focuses on using a Naive Bayes classification algorithm to assess political party and public Twitter sentiment. A Granger causality analysis is then introduced to investigate the hypothesis that BREXIT political and public sentiment, as measured by the twitter sentiment time series, is indicative of changes in the GBP/EUR Fx and FTSE 100 Index. Our results indicate that the accuracy of the 'Article 50' scenario had the single biggest effect on short run dynamics on the FTSE 100 index, additionally the 'Norway' BREXIT strategy has a marginal effect on the FTSE 100 index whilst there was no significant causation to the GBP/EUR Fx.",
keywords = "Data mining, Stock Market, Twitter sentiment, Web intelligence",
author = "James Usher and Lucia Morales and Pierpaolo Dondio",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2nd IEEE International Conference on Artificial Intelligence and Knowledge Engineering, AIKE 2019 ; Conference date: 03-06-2019 Through 05-06-2019",
year = "2019",
month = jun,
doi = "10.1109/AIKE.2019.00017",
language = "English",
series = "Proceedings - IEEE 2nd International Conference on Artificial Intelligence and Knowledge Engineering, AIKE 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "51--54",
booktitle = "Proceedings - IEEE 2nd International Conference on Artificial Intelligence and Knowledge Engineering, AIKE 2019",
address = "United States",
}