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.
|Pages (from-to)||121 - 125|
|Journal||Communications in Computer and Information Science|
|Publication status||Published - 1 Jun 2016|
|Event||3rd Semantic Web Challenges Conference: ESWC 2016 - Kreta, Heraklion, Greece|
Duration: 29 May 2016 → 2 Jun 2016