Skip to Main content Skip to Navigation
Conference papers

SMACk: An Argumentation Framework for Opinion Mining

Mauro Dragoni 1, * Célia da Costa Pereira 2 Andrea G. B. Tettamanzi 3 Serena Villata 3 
* Corresponding author
3 WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics
CRISAM - Inria Sophia Antipolis - Méditerranée , Laboratoire I3S - SPARKS - Scalable and Pervasive softwARe and Knowledge Systems
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.
Document type :
Conference papers
Complete list of metadata

Cited literature [4 references]  Display  Hide  Download
Contributor : Andrea G. B. Tettamanzi Connect in order to contact the contributor
Submitted on : Tuesday, August 16, 2016 - 11:51:26 AM
Last modification on : Thursday, August 4, 2022 - 4:58:56 PM
Long-term archiving on: : Thursday, November 17, 2016 - 10:45:28 AM


Publisher files allowed on an open archive


  • HAL Id : hal-01353931, version 1



Mauro Dragoni, Célia da Costa Pereira, Andrea G. B. Tettamanzi, Serena Villata. SMACk: An Argumentation Framework for Opinion Mining. International Joint Conference on Artificial Intelligence (IJCAI), Jul 2016, New York, NY, United States. pp.4242-4243. ⟨hal-01353931⟩



Record views


Files downloads