Machine learning in automated text categorization
ACM Computing Surveys (CSUR)
A sentimental education: sentiment analysis using subjectivity summarization based on minimum cuts
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
The automatic creation of literature abstracts
IBM Journal of Research and Development
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In on-line reviews, authors often use a short passage to describe the overall feeling about a product or a service. A review as a whole can mention many details not in line with the overall feeling, so capturing this key passage is important to understand the overall sentiment of the review. This paper investigates the use of extractive summarisation in the context of sentiment classification. The aim is to find the summary sentence, or the short passage, which gives the overall sentiment of the review, filtering out potential noisy information. Experiments on a movie review data-set show that subjectivity detection plays a central role in building summaries for sentiment classification. Subjective extracts carry the same polarity of the full text reviews, while statistical and positional approaches are not able to capture this aspect.