Zagibalov, Taras and Carroll, John (2008) Automatic seed word selection for unsupervised sentiment classification of Chinese text. In: 22nd International Conference on Computational Linguistics (COLING), Manchester, UK.
Full text not available from this repository.Abstract
We describe and evaluate a new method of automatic seed word selection for unsupervised sentiment classification of product reviews in Chinese. The whole method is unsupervised and does not require any annotated training data; it only requires information about commonly occurring negations and adverbials. Unsupervised techniques are promising for this task since they avoid problems of domain-dependency typically associated with supervised methods. The results obtained are close to those of supervised classifiers and sometimes better, up to an F1 of 92%.
Item Type: | Conference or Workshop Item (Paper) |
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Schools and Departments: | School of Engineering and Informatics > Informatics |
Depositing User: | John Carroll |
Date Deposited: | 06 Feb 2012 21:18 |
Last Modified: | 13 Apr 2012 13:19 |
URI: | http://sro.sussex.ac.uk/id/eprint/30705 |