Expanding Corpora for Chinese Polarity Classification via Opinion Paraphrase Generation

摘要

Although much progress has been made to date on sentiment classification, lacking annotated corpora remains a problem. In this paper we propose to expand corpora for Chinese polarity classification via opinion paraphrase generation. To this end, we first exploit three strategies for opinion paraphrase generation, namely sentences re-ordering, opinion element substitution and explicit attribution implying. To improve the quality of the generated opinion paraphrases, we define four criteria for opinion paraphrase evaluation and thus present a filtering algorithm to discard improper opinion paraphrase candidates. To assess the proposed method, we further apply the expanded corpus to a SVM classifier for polarity classification. The experimental results show that the generated opinion paraphrases are beneficial to polarity classification.