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Mining opinion targets and opinion words from online reviews

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Abstract

Extracting opinion targets (features) and opinion words is a main task in aspect-based level sentiment analysis. In this paper, we have proposed a hybrid approach for mining features and opinion words based on an upgraded “double propagation” algorithm by adding rules that explore the semantic relations between many parts of speech in sentences, some regular expression rules and ontologies. We employed HITS algorithm to prune features. In our experiments on multiple data sets, we showed that our approach gives perfectly acceptable results.

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Acknowledgement

This paper was supported by the research Project C2016-20-32 funded by Vietnam National University Ho Chi Minh City (VNU-HCM).

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Authors and Affiliations

  1. Faculty of Computer Science and Engineering, Ho Chi Minh City University of Technology - VNU-HCM, Ho Chi Minh City, Vietnam

    Thien Khai Tran & Tuoi Thi Phan

  2. Faculty of Information Technology, Ho Chi Minh City University of Foreign Languages and Information Technology, Ho Chi Minh City, Vietnam

    Thien Khai Tran

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  1. Thien Khai Tran
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  2. Tuoi Thi Phan
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Correspondence to Thien Khai Tran.

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Tran, T.K., Phan, T.T. Mining opinion targets and opinion words from online reviews. Int. j. inf. tecnol. 9, 239–249 (2017). https://doi.org/10.1007/s41870-017-0032-9

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  • DOI: https://doi.org/10.1007/s41870-017-0032-9

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