Abstract
A significant amount of research on the intersection of sentiment analysis and social media platforms has been published in the past few years. While previous studies have focused on methods to identify the polarity of online posts, little has been done in terms of using the impact of such posts to enhance the discovery and description of trends in real time. Here, we present a tool for the retrieval and analysis of microblogging posts in real time. We have gathered a large sample of tweets related to the 2017 UK General Election. We introduce a novel classification of the polarity of sentiments, considering the correlation between words, events and sentiments.
DOI
10.1109/CSCI.2017.253
Publication Date
2017-12-14
Event
4th Annual Conference on Computational Science & Computational Intelligence (CSCI'17)
Publication Title
ISBN: 1-60132-469-3
Publisher
IEEE
ISBN
978-1-5386-2652-8
Embargo Period
2024-11-22
Recommended Citation
Plummer, M., Palomino, M., & Masala, G. (2017) 'Analysing the Sentiment Expressed by Political Audiences on Twitter: The case of the 2017 UK General Election', ISBN: 1-60132-469-3, . IEEE: Available at: https://doi.org/10.1109/CSCI.2017.253
