Before revision:  Since the labeled data may be from multiple sources, multi-source domain adaptation (MDA) would be more practical to exploit the complementary information from different domains. Existing MDA methods might fail to extract some discriminative features in the target domain that are related to sentiment, neglect the correlations of different sources as well as the distribution difference among different sub-domains even in the same source, and cannot reflect the varying optimal weighting during different training stages.
After revision:  Since the labeled data may be from multiple sources, multi-source domain adaptation (MDA) methods either fail to extract some discriminative features in the target domain that are related to sentiment, neglect the correlations of different sources as well as the distribution difference among different sub-domains even in the same source, and cannot reflect the varying optimal weighting during different training stages.