Using Sentiment Analysis of Twitter Data for Determining Popularity of City Locations

Abstract

The paper considers mining and analyzing data generated by Twitter social network, regarding content classification, language determination and sentiment analysis of tweets. Analyzes are based on geospatial tweets collected in timespan of four months within region Vracar in Belgrade, Serbia. All of collected data is first being preprocessed, filtered and classified by given criteria, by using "Twitter search engine" (TSE) application, that has been upgraded in order to detect tweet language and execute sentiment analysis of the tweets written in English. This type of analysis can be used for determining popularity of city locations of interest and public spaces in general.