Geospatial sentiment analysis using twitter data for UK-EU referendum. Issue 1 (2nd January 2018)

• Record Type: Journal Article
• Authors: Agarwal, Amit; Singh, Ritu; Toshniwal, Durga
• Is Part Of: Journal of information & optimization sciences. Volume 39:Issue 1(2018)
• Page Start: 303
• Page End: 317
• Publication Date: 2018-01-02
• Subjects: Brexit -- Geospatial -- temporal analysis and sentiment analysis -- social media -- UK-EU Referendum; 68T30; Electronic data processing -- Periodicals; Information science -- Periodicals; Mathematical optimization -- Periodicals; 519.6
• DOI: 10.1080/02522667.2017.1374735
• Languages: English
• ISSNs: 0252-2667

Abstract

Abstract: Brexit i.e. "British Exit" is one of the major events in the history of economics and British politics. When EU referendum took place, 52% of votes were in favor of United Kingdom leaving the European Union. This was a major event affecting the overall economy of Britain and was also one of the most talked about events. Twitter is a social network platform where users from all over the world discussed a lot about Brexit and British politics. Analysis of such user generated text can reveal a lot about the event and what people think of it. Sentiment analysis is a trending technique to get insights from any written text. Our aim in this study is to analyze the tweets geospatially and then perform Geo-spatial Sentiment analysis based on the location of the events verses the geospatial tweets distribution for that particular event on global level. Also shows the keywords and hashtags were mostly used by people during that time and how they were being used i.e. which hashtag was used positively, which one was used negatively and which one carried neutral sentiment with itself. This study also tries to find out the British politicians who were being talked about the most and what people think of them sentimentally. Also, the tweets intended for these famous British politicians are analyzed geospatially and their sentiment distribution is visualized. The geospatial sentiment analysis of the whole dataset for "leave" and "remain" tags is also plotted on the atlas map.