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Student: N/A
Supervisor: Manfred Klenner
Tweets are a very special kind of text. Determining whether a tweet is positive, negative or neutral is not solely lexically dependent: hashtags, emoticons and other creative constructs are also significant. A supervised sentiment analysis for tweets requires the generation of feature vectors to be able to train a machine learning process. To do this, an existing Python module called Pattern can be used for downloading tweets and providing various machine learning techniques.
Automatic analysis of whether a tweet is positive, negative or neutral with German as a target language.
Alexandra Balahur (2013). Sentiment Analysis in Social Media Texts. In: 4th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis