We describe a Twitter sentiment analysis system developed by combining a rule-based classifier with supervised learning. We submitted our results for the message-level subtask in SemEval 2015 Task 10, and achieved a F 1 -score of 57.06%. The rule-based classifier is based on rules that are dependent...
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