Using Tweets for Assigning Sentiments to Regions

Erik Tjong Kim Sang

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Abstract

We derive a sentiment lexicon for Dutch tweets and apply the lexicon for classifying Dutch tweets as positive, negative or neutral. The
classifier enables us to test what regions in the Netherlands and Flanders express more positive sentiment on Twitter than others. The
results reveal sentiment differences between Flemish and Dutch provinces, and expose municipalities which are a lot more negative than
their neighborhood. The results of this study can be used for finding areas with local issues that might be expressed in tweets.
Original languageEnglish
Pages64-67
Number of pages4
Publication statusPublished - 26 May 2014

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