Visualized Emotion Ontology: a model for representing visual cues of emotions

Abstract

BackgroundHealthcare services, particularly in patient-provider interaction, often involve highly emotional situations, and it is important for physicians to understand and respond to their patients’ emotions to best ensure their well-being.MethodsIn order to model the emotion domain, we have created the Visualized Emotion Ontology (VEO) to provide a semantic definition of 25 emotions based on established models, as well as visual representations of emotions utilizing shapes, lines, and colors.ResultsAs determined by ontology evaluation metrics, VEO exhibited better machine-readability (z=1.12), linguistic quality (z=0.61), and domain coverage (z=0.39) compared to a sample of cognitive ontologies. Additionally, a survey of 1082 participants through Amazon Mechanical Turk revealed that a significantly higher proportion of people agree than disagree with 17 out of our 25 emotion images, validating the majority of our visualizations.ConclusionFrom the development, evaluation, and serialization of the VEO, we have defined a set of 25 emotions using OWL that linked surveyed visualizations to each emotion. In the future, we plan to use the VEO in patient-facing software tools, such as embodied conversational agents, to enhance interactions between patients and providers in a clinical environment.

VEO-Engine: Interfacing and Reasoning with an Emotion Ontology for Device Visual Expression

“…Based on our previous VEO work [9,10], we developed VEO-Engine, a software library that interfaces with the emotion ontology. The VEO-Engine was able to query for visualizations associated with an emotion, and it was able to deduce an emotion based on sample input parameters.…”

“…Lastly, we created visualizations based on evidence from published research for each of the emotions described, and each visualization linked to an emotion using the ontology. Overall, the VEO semantically defined and visualized 25 emotions [9]. …”

“…The initial assessments yielded a structurally and semantically sound ontology, compared with other cognitive-related ontologies, and the individuals surveyed ( n = 1082) agreed that most visualizations represented specific emotions [9]. …”

Electronic Negotiation and Behavioral Elements

“…An ontology is a way to characterize concepts and ideas, and show the relationships among them. The corpus of knowledge generated by ontologies has been useful in diverse areas ranging from manufacturing (Sormaz and Sarkar 2019) to medicine (Lin et al 2018), and has moreover been also suggested for ENS as well. For example, Tamma et al (2005) propose an ontology for supporting a wide variety of negotiation mechanisms and protocols.…”

“…These works have also been used by Sykora et al (2013) to derive an emotion-ontology that can be applied to analyze social-media messages. For the medical domain, Lin et al (2018) derive an emotion-ontology using 25 types. Likewise, Kelly (2014) have proposed an ontology for power and leadership, and Huang and Fox (2006) have proposed a formal-logic axiomatic theory of trust in the form of an ontology, showing how it can be potentially used for Web-services trust.…”