Analysis and visualization of subjectivity and polarity of Twitter location data

Abstract

Increased use of Twitter by a large number of users has resulted in an unprecedented growth in the generation of user created data. This data is now being analyzed in various areas of research including that of user sentiment and behavior analysis during general elections. Rise in the use of Twitter for electoral campaigning has increased interest of researchers in this area. However while studies have utilized factors such as sentiment and frequency of tweets to evaluate candidate favorability, little research has been conducted in analyzing Twitter location data. This paper makes two major contributions. First, it studies the subjectivity and polarity of Twitter data based on the location of the tweets. Findings from this research will enable further fine grained analysis of Twitter data by using the location variable, allowing for more accurate results of user sentiment and behavior analysis. Second, we present a web-based system which can enable in the collection of Twitter data, extraction of the location, perform data analysis and then to plot them on a maps for visualization. We employ US presidential election data of 2016 as a case study to test our research questions and to demonstrate our results utilizing this web-based system.