Predicting the Brexit Vote by tracking and classifying public opinion using Twitter data

• Main Authors: AMADOR DIAZ LOPEZ, Julio C., COLLIGNON-DELMAR, Sofia, BENOIT, Kenneth, MATSUO, Akitaka
• 格式: text
• 語言: English
• 出版: Institutional Knowledge at Singapore Management University 2017
• 主題: Models and Methods; Political Science; Social Media
• 在線閱讀: https://ink.library.smu.edu.sg/soss_research/3991; https://ink.library.smu.edu.sg/context/soss_research/article/5249/viewcontent/BrexitVote_2017_pv.pdf

We use 23M Tweets related to the EU referendum in the UK to predict the Brexit vote. In particular, we use user-generated labels known as hashtags to build training sets related to the Leave/Remain campaign. Next, we train SVMs in order to classify Tweets. Finally, we compare our results to Internet...