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This paper describes state-of-the-art statistical systems for automatic sentiment analysis of tweets. In a Semeval-2014 shared task (Task 9), our submissions obtained highest scores in the term-level sentiment classification subtask on both the 2013 and 2014 tweets test sets. In the message-level sentiment classification task, our submissions obtained highest scores on the Live-Journal blog posts test set, sarcastic tweets test set, and the 2013 SMS test set. These systems build on ourdoi:10.3115/v1/s14-2077 dblp:conf/semeval/ZhuKM14 fatcat:ed6a4himtfcehcbixnh6mscxbi