Tapping Twitter Data for Analyzing and Visualizing Public Sentiments on Censorship

The main objective of this research study is to analyse and visualize Twitter data with tags “#Censorship”. A connection was established with twitter using Twitter API, and receiving the tweets on Google Spreadsheets. Data visualization was performed using various tools such as Voyant Tools, Tableau, Google Spreadsheet and Orange in order to generate different visualizations based upon, language, geographical areas, retweets etc. The sentiment analysis was performed for the sentiments that were attached to the given set of data by the public in their respective tweets. The 23680 tweets were retrieved during the data collection time and there were 13,771 retweets out of these tweets. The most popular application for using twitter by the users was Twitter Web Client which constituted of the 33.67% (7972 tweets); the second most popular app was Android with 23.61% (5592 Tweets) and Twitter for iPhone stayed at third place with a share of 20.07% (4753 Tweets). The most frequent used Hashtags (#) in the tweets were #Twitter, #Facebook, #Google, #YouTube etc. Results show that negative tweets are enormously higher than the neutral sentiments