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2016 | OriginalPaper | Buchkapitel

Exploiting Propositions for Opinion Mining

verfasst von : Andi Rexha, Mark Kröll, Mauro Dragoni, Roman Kern

Erschienen in: Semantic Web Challenges

Verlag: Springer International Publishing

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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 drive 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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Literatur
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Zurück zum Zitat Chung, J.K.-C., Wu, C.-E., Tsai, R.T.-H.: Polarity detection of online reviews using sentiment concepts: NCU IISR Team at ESWC-14 challenge on concept-level sentiment analysis. In: Presutti, V., et al. (eds.) SemWebEval 2014. CCIS, vol. 475, pp. 53–58. Springer, Heidelberg (2014). doi:10.1007/978-3-319-12024-9_7 Chung, J.K.-C., Wu, C.-E., Tsai, R.T.-H.: Polarity detection of online reviews using sentiment concepts: NCU IISR Team at ESWC-14 challenge on concept-level sentiment analysis. In: Presutti, V., et al. (eds.) SemWebEval 2014. CCIS, vol. 475, pp. 53–58. Springer, Heidelberg (2014). doi:10.​1007/​978-3-319-12024-9_​7
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Metadaten
Titel
Exploiting Propositions for Opinion Mining
verfasst von
Andi Rexha
Mark Kröll
Mauro Dragoni
Roman Kern
Copyright-Jahr
2016
DOI
https://doi.org/10.1007/978-3-319-46565-4_9

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