title: Sentiments analysis at conceptual level making use of the Narrative Knowledge Representation Language.
abstract: This paper illustrates some of the knowledge representation structures and inference procedures proper to a high-level, fully implemented conceptual language, NKRL (Narrative Knowledge Representation Language). The aim is to show how these tools can be used to deal, in a sentiment analysis/opinion mining context, with some common types of human (and non-human) "behaviors". These behaviors correspond, in particular, to the concrete, mutual relationships among human and non-human characters that can be expressed under the form of non-fictional and real-time "narratives" (i.e., as logically and temporally structured sequences of "elementary events").
authors.affiliation: Sorbonne University-STIH Laboratory, 1, rue Victor Cousin-75005 Paris, France. Electronic address: zarri@noos.fr.
authors.forename: Gian Piero
authors.initials: GP
authors.lastname: Zarri
mesh_terms: D004644:Emotions; D006801:Humans; D007802:Language; D033262:Narration; D009323:Natural Language Processing; D012919:Social Behavior
keywords: Behaviors; Narratives; Ontologies of events; Querying and inference techniques; Representation of deep sentiments; Standard ontologies