Exploiting Propositions for Opinion Mining

Andi Rexha, Mark Kröll, Mauro Dragoni, Roman Kern

Research output: Contribution to journalConference articlepeer-review


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.
Original languageEnglish
Pages (from-to)121 - 125
JournalCommunications in Computer and Information Science
Publication statusPublished - 1 Jun 2016
Event3rd Semantic Web Challenges Conference: ESWC 2016 - Kreta, Heraklion, Greece
Duration: 29 May 20162 Jun 2016


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