The extraction of the relevant and debated opinions from online social media and commercial websites is an emerging task in the opinion mining research field. Its growing relevance is mainly due to the impact of exploiting such techniques in different application domains from social science analysis to personal advertising. In this demo, we present our opinion summary application built on top of an ar-gumentation framework, a standard AI framework whose value is to exchange, communicate and resolve possibly conflicting viewpoints in distributed scenarios. We show how our application is able to extract relevant and debated opinions from a set of documents containing user-generated content from online commercial websites.

SMACk: An Argumentation Framework for Opinion Mining

Dragoni, Mauro;
2016-01-01

Abstract

The extraction of the relevant and debated opinions from online social media and commercial websites is an emerging task in the opinion mining research field. Its growing relevance is mainly due to the impact of exploiting such techniques in different application domains from social science analysis to personal advertising. In this demo, we present our opinion summary application built on top of an ar-gumentation framework, a standard AI framework whose value is to exchange, communicate and resolve possibly conflicting viewpoints in distributed scenarios. We show how our application is able to extract relevant and debated opinions from a set of documents containing user-generated content from online commercial websites.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11582/307302
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