Abstract
In this paper, we analyze weather social sentiments can be utilized for the prediction of election results. In particular, we analyze Twitter sentiments about Brexit and United Kingdom (UK) politicians. Twitter is the essential social network for sentiments analyzing and it provides useful information for mining data. Through periods, we collected Twitter data about Brexit and UK politicians using Twitter Application Program interface (API). First, we cleaned and pre-processed Tweet data for sentiment analysis. Then, we create a Twitter search and sentiment visualization interface using python. Python provides useful libraries for sentiment analysis and graphical presentations. Finally, we analyze the changing opinions about Brexit and UK politicians using sentiments. In particular, in advance, we were able to correctly predict the UK parliament voting results in January 2019. In this paper, we discuss Twitter data collection, Twitter sentiment search/visualization interface and detailed sentiment analysis results about Brexit and UK politicians.
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