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Sentiment classification on polarity reviews: an empirical study using rating-based features

Nguyen, Dai Quoc; Nguyen, Dat Quoc; Vu, Thanh and Pham, Son Bao (2014). Sentiment classification on polarity reviews: an empirical study using rating-based features. In: Proceedings of the 5th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, pp. 128–135.

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Abstract

We present a new feature type named rating-based feature and evaluate the contribution of this feature to the task of document-level sentiment analysis. We achieve state-of-the-art results on two publicly available standard polarity movie datasets: on the dataset consisting of 2000 reviews produced by Pang and Lee (2004) we obtain an accuracy of 91.6% while it is 89.87% evaluated on the dataset of 50000 reviews created by Maas et al. (2011). We also get a performance at 93.24% on our own dataset consisting of 233600 movie reviews, and we aim to share this dataset for further research in sentiment polarity analysis task.

Item Type: Conference or Workshop Item
Copyright Holders: 2014 The Authors
Project Funding Details:
Funded Project NameProject IDFunding Body
Not SetQG.14.04Vietnam National University, Hanoi
Extra Information: Held in conjunction with the ACL 2014 Conference
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
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Item ID: 40128
Depositing User: Thanh Vu
Date Deposited: 12 May 2014 13:01
Last Modified: 02 May 2018 13:59
URI: http://oro.open.ac.uk/id/eprint/40128
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