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Semantic Web Evaluation Challenge

SemWebEval 2017: Semantic Web Challenges pp 166–175Cite as

Opinion Mining with a Clause-Based Approach

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 769))

Abstract

With different social media and commercial platforms, users express their opinion about products in a textual form. Automatically extracting the polarity (i.e. whether the opinion is positive or negative) of a user can be useful for both actors: the online platform incorporating the feedback to improve their product as well as the client who might get recommendations according to his or her preferences. Different approaches for tackling the problem, have been suggested mainly using syntactic features. The “Challenge on Semantic Sentiment Analysis” aims to go beyond the word-level analysis by using semantic information. In this paper we propose a novel approach by employing the semantic information of grammatical unit called preposition. We try to derive the target of the review from the summary information, which serves as an input to identify the proposition in it. Our implementation relies on the hypothesis that the proposition expressing the target of the summary, usually containing the main polarity information.

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Acknowledgment

This work is funded by the KIRAS program of the Austrian Research Promotion Agency (FFG) (project number 840824). The Know-Center is funded within the Austrian COMET Program under the auspices of the Austrian Ministry of Transport, Innovation and Technology, the Austrian Ministry of Economics and Labour and by the State of Styria. COMET is managed by the Austrian Research Promotion Agency FFG.

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Authors and Affiliations

  1. Know-Center GmbH, Graz, Austria

    Andi Rexha, Mark Kröll & Roman Kern

  2. FBK-IRST, Trento, Italy

    Mauro Dragoni

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  1. Andi Rexha
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  2. Mark Kröll
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  3. Mauro Dragoni
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  4. Roman Kern
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Correspondence to Mauro Dragoni .

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Editors and Affiliations

  1. Fondazione Bruno Kessler , Povo, Trento, Italy

    Mauro Dragoni

  2. University of Oxford , Oxford, United Kingdom

    Monika Solanki

  3. Linköping University , Linköping, Sweden

    Eva Blomqvist

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Rexha, A., Kröll, M., Dragoni, M., Kern, R. (2017). Opinion Mining with a Clause-Based Approach. In: Dragoni, M., Solanki, M., Blomqvist, E. (eds) Semantic Web Challenges. SemWebEval 2017. Communications in Computer and Information Science, vol 769. Springer, Cham. https://doi.org/10.1007/978-3-319-69146-6_15

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  • DOI: https://doi.org/10.1007/978-3-319-69146-6_15

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