A Web Search Enhanced Feature Extraction Method for Aspect-Based Sentiment Analysis for Turkish Informal Texts

Date

2016-09-08

Author

Kama, Batuhan
ÖZTÜRK, MURAT
Karagöz, Pınar
Toroslu, İsmail Hakkı
Ozay, Ozcan

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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In this article, a new unsupervised feature extraction method for aspect-based sentiment analysis is proposed. This method improves the performance of frequency based feature extraction by using an online search engine. Although frequency based feature extraction methods produce good precision and recall values on formal texts, they are not very successful on informal texts. Our proposed algorithm takes the features of items suggested by frequency based feature extraction methods, then, eliminates the features which do not co-occur with the item, whose features are sought, on the Web. Since the proposed method constructs the candidate feature set of the item from the Web, it is domain-independent. The results of experiments reveal that for informal Turkish texts, much higher performance than frequency based method is achieved.

Subject Keywords

Computer Science, Artificial Intelligence, Computer Science, Information Systems, Computer Science, Theory & Methods

URI

https://hdl.handle.net/11511/47860

DOI

https://doi.org/10.1007/978-3-319-43946-4_15

Collections

Department of Computer Engineering, Conference / Seminar

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Citation Formats

B. Kama, M. ÖZTÜRK, P. Karagöz, İ. H. Toroslu, and O. Ozay, “A Web Search Enhanced Feature Extraction Method for Aspect-Based Sentiment Analysis for Turkish Informal Texts,” 2016, vol. 9829, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/47860.