Modeling Review Comments.

ACL '12: Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1(2012)

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摘要
Writing comments about news articles, blogs, or reviews have become a popular activity in social media. In this paper, we analyze reader comments about reviews. Analyzing review comments is important because reviews only tell the experiences and evaluations of reviewers about the reviewed products or services. Comments, on the other hand, are readers' evaluations of reviews, their questions and concerns. Clearly, the information in comments is valuable for both future readers and brands. This paper proposes two latent variable models to simultaneously model and extract these key pieces of information. The results also enable classification of comments accurately. Experiments using Amazon review comments demonstrate the effectiveness of the proposed models.
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关键词
Amazon review comment,Analyzing review comment,future reader,key piece,latent variable model,news article,popular activity,proposed model,reader comment,social media
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