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Sentiment classification is a crucial task in sentiment analysis, and has received significant attention from researchers. Previous studies have focused on using several techniques to solve this problem. However, to the best of our knowledge, none of these works has fully investigated the exploitation and the manipulation of contextual information in the text, or taken advantage of the combined power of state-of-theart models. In this paper, we propose an effective ensemble learning model fordoi:10.1109/access.2020.3004180 fatcat:ro74lbephjgkfj3llir3lqz7y4