EFO: the Emotion Frame Ontology

TL;DR

This paper introduces the Emotion Frame Ontology (EFO), an OWL-based framework that models emotions as semantic frames, enabling cross-theory integration, automated inference, and multimodal emotion analysis.

Contribution

It presents a novel OWL ontology for emotions that aligns with foundational ontologies and supports modeling multiple emotion theories and multimodal datasets.

Findings

Successfully modeled Ekman's Basic Emotions theory as an EFO module

Automated inference capabilities demonstrated on emotion representations

Integrated multimodal emotion data for crossmodal analysis

Abstract

Emotions are a subject of intense debate in various disciplines. Despite the proliferation of theories and definitions, there is still no consensus on what emotions are, and how to model the different concepts involved when we talk about - or categorize - them. In this paper, we propose an OWL frame-based ontology of emotions: the Emotion Frames Ontology (EFO). EFO treats emotions as semantic frames, with a set of semantic roles that capture the different aspects of emotional experience. EFO follows pattern-based ontology design, and is aligned to the DOLCE foundational ontology. EFO is used to model multiple emotion theories, which can be cross-linked as modules in an Emotion Ontology Network. In this paper, we exemplify it by modeling Ekman's Basic Emotions (BE) Theory as an EFO-BE module, and demonstrate how to perform automated inferences on the representation of emotion situations. EFO-BE has been evaluated by lexicalizing the BE emotion frames from within the Framester knowledge graph, and implementing a graph-based emotion detector from text. In addition, an EFO integration of multimodal datasets, including emotional speech and emotional face expressions, has been performed to enable further inquiry into crossmodal emotion semantics.