Sentiment Analysis for Tweets in Swedish : Using a sentiment lexicon with syntactic rules

Sentiment Analysis refers to the extraction of opinion and emotion from data. In its simplest form, an application estimates a sentence and labels it with a positive or negative sentiment score. One way of doing this is through a lexicon of sentiment-laden words, each annotated with its respective polarity. Tweets are a specific kind of data that has spurred interest in researchers, since they tend to carry opinions on various topics, such as political parties, stocks or commercial brands. Tools and libraries have been developed for analyzing the sentiment of tweets and other kinds of data, but mainly for the English language. This report investigates ways of efficiently analyzing the sentiment of tweets written in Swedish. A sentiment lexicon translated from English to Swedish, together with different combinations of syntax rules, is tested on a labeled set of tweets. Machine-translating a lexicon did not provide a fully satisfying result for sentiment analysis in Swedish. However, the resulting model could be used as a base for constructing a more successful tool