Abstract
Natural language processing tools are mostly developed for and optimized on newspaper texts, and often show a substantial performance drop when applied to other types of texts such as Twitter feeds, chat data or Internet forum posts. We explore a range of easy-to-implement methods of adapting existing part-of-speech taggers to improve their performance on Internet texts. Our results show that these methods can improve tagger performance substantially.
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