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Domain adaptation is an important research topic in sentiment analysis area. Existing domain adaptation methods usually transfer sentiment knowledge from only one source domain to target domain. In this paper, we propose a new domain adaptation approach which can exploit sentiment knowledge from multiple source domains. We first extract both global and domain-specific sentiment knowledge from the data of multiple source domains using multi-task learning. Then we transfer them to target domaindoi:10.18653/v1/p16-1029 dblp:conf/acl/WuH16 fatcat:pvp3dtw7fjby5arqbde7ktntby