Abstract: The scalability problem becomes a bottleneck for traditional stand-alone sentiment classification algorithms due to the massive data．We implemented feature extraction,feature weighting and classification algorithms involved in sentiment classification task by using MapReduce technique on Hadoop platform．We evaluated our proposed paralle-lized sentiment classification algorithms on real data sets in terms of precision and time costs．Experimental results show the effectiveness of these parallelized sentiment classification algorithms and also provide valuable references for users to select suitable sentiment classification algorithms according to user requirements.

Key words: Sentiment classification,Hadoop,Cloud computing,MapReduce