Abstract
This paper fills a gap in aspect-based sentiment analysis and aims to present a new method for preparing and analysing texts concerning opinion and generating user-friendly descriptive reports in natural language. We present a comprehensive set of techniques derived from Rhetorical Structure Theory and sentiment analysis to extract aspects from textual opinions and then build an abstractive summary of a set of opinions. Moreover, we propose aspect-aspect graphs to evaluate the importance of aspects and to filter out unimportant ones from the summary. Additionally, the paper presents a prototype solution of data flow with interesting and valuable results. The proposed method’s results proved the high accuracy of aspect detection when applied to the gold standard dataset.
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Acknowledgment
The work was partially supported by the National Science Centre grants DEC-2016/21/N/ST6/02366 and DEC-2016/21/D/ST6/02948, and from the European Unions Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 691152 (RENOIR project).
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Augustyniak, Ł., Rajda, K., Kajdanowicz, T. (2017). Method for Aspect-Based Sentiment Annotation Using Rhetorical Analysis. In: Nguyen, N., Tojo, S., Nguyen, L., Trawiński, B. (eds) Intelligent Information and Database Systems. ACIIDS 2017. Lecture Notes in Computer Science(), vol 10191. Springer, Cham. https://doi.org/10.1007/978-3-319-54472-4_72
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DOI: https://doi.org/10.1007/978-3-319-54472-4_72
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