Combining Argumentation and Aspect-Based Opinion Mining: The SMACk System

Mauro Dragoni (1) , Célia da Costa Pereira (2) , Andrea G. B. Tettamanzi (3) , Serena Villata (3)

1 FBK - Fondazione Bruno Kessler [Trento, Italy]
2 Laboratoire I3S - SPARKS - Scalable and Pervasive softwARe and Knowledge Systems
3 WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics

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 paper, we present SMACk, our opinion summary system built on top of an argumentation framework with the aim to exchange, communicate and resolve possibly conflicting viewpoints. SMACk allows the user to extract debated opinions from a set of documents containing user-generated content from online commercial websites, and to automatically identify the mostly debated positive aspects of the issue of the debate, as well as the mostly debated negative ones. The key advantage of such a framework is the combination of different methods, i.e., formal argumentation theory and natural language processing, to support users in making more informed decisions, e.g., in the context of online purchases.

Mots clés: Argumentation Theory; Opinion Mining; Aspect Extraction

Domaines: Intelligence artificielle [cs.AI]

Mauro Dragoni, Célia da Costa Pereira, Andrea G. B. Tettamanzi, Serena Villata. Combining Argumentation and Aspect-Based Opinion Mining: The SMACk System. AI Communications, 2018, 31 (1), pp.75 - 95. ⟨10.3233/AIC-180752⟩. ⟨hal-01721538⟩