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Method for Aspect-Based Sentiment Annotation Using Rhetorical Analysis

  • Łukasz Augustyniak
  • Krzysztof Rajda
  • Tomasz Kajdanowicz
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10191)

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.

Keywords

Sentiment analysis Opinion mining Aspect-based sentiment analysis Rhetorical analysis Rhetorical Structure Theory 

Notes

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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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Łukasz Augustyniak
    • 1
  • Krzysztof Rajda
    • 2
  • Tomasz Kajdanowicz
    • 1
  1. 1.Department of Computational IntelligenceWroclaw University of TechnologyWroclawPoland
  2. 2.Kenaz TechnologiesLesznoPoland

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