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	title        = {RTRGO: Enhancing the GU-MLT-LT System for Sentiment Analysis of Short Messages},
	abstract     = {This paper describes the enhancements made to our GU-MLT-LT system (Günther and Furrer, 2013) for the SemEval-2014 re-run of the SemEval-2013 shared task on sentiment analysis in Twitter. The changes include the usage of a Twitter-specific tokenizer, additional features and sentiment lexica, feature weighting and random subspace learning. The improvements result in an increase of 4.18 F-measure points on this year’s Twitter test set, ranking 3rd.
	booktitle    = {Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014) August 23-24, 2014 Dublin, Ireland},
	author       = {Günther, Tobias and Vancoppenolle, Jean and Johansson, Richard},
	year         = {2014},
	ISBN         = {978-1-941643-24-2},
	pages        = {497--502},