Abstract
Expression of opinion depends on the domain. For instance, some words, called here multi-polarity words, have dierent polarities across domain. Therefore, a classifier trained on one domain and tested on another one will not perform well without adaptation. This article presents a study of the influence of these multi-polarity words on domain adaptation for automatic opinion classification. We also suggest an exploratory method for detecting them without using any label in the target domain. We show as well how these multi-polarity words can improve opinion classification in an open-domain corpus.
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