Creating subjective and objective sentence classifiers from unannotated texts

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Abstract

This paper presents the results of developing subjectivity classifiers using only unannotated texts for training. The performance rivals that of previous supervised learning approaches. In addition, we advance the state of the art in objective sentence classification by learning extraction patterns associated with objectivity and creating objective classifiers that achieve substantially higher recall than previous work with comparable precision. © Springer-Verlag Berlin Heidelberg 2005.

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Wiebe, J., & Riloff, E. (2005). Creating subjective and objective sentence classifiers from unannotated texts. In Lecture Notes in Computer Science (Vol. 3406, pp. 486–497). Springer Verlag. https://doi.org/10.1007/978-3-540-30586-6_53

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