Ontology for cultural variations in interpersonal communication: Building on theoretical models and crowdsourced knowledge

Abstract

The domain of cultural variations in interpersonal communication is becoming increasingly important in various areas, including human–human interaction (e.g., business settings) and human–computer interaction (e.g., during simulations, or with social robots). User‐generated content (UGC) in social media can provide an invaluable source of culturally diverse viewpoints for supporting the understanding of cultural variations. However, discovering and organizing UGC is notoriously challenging and laborious for humans, especially in ill‐defined domains such as culture. This calls for computational approaches to automate the UGC sensemaking process by using tagging, linking, and exploring. Semantic technologies allow automated structuring and qualitative analysis of UGC, but are dependent on the availability of an ontology representing the main concepts in a specific domain. For the domain of cultural variations in interpersonal communication, no ontological model exists. This paper presents the first such ontological model, called AMOn+, which defines cultural variations and enables tagging culture‐related mentions in textual content. AMOn+ is designed based on a novel interdisciplinary approach that combines theoretical models of culture with crowdsourced knowledge (DBpedia). An evaluation of AMOn+ demonstrated its fitness‐for‐purpose regarding domain coverage for annotating culture‐related concepts mentioned in text corpora. This ontology can underpin computational models for making sense of UGC.

An activity theory based approach for ontological modelling of collaborative logistics process dynamics

“…In addition, building an ontology often depends on 'knowledge and experience' due to a lack of rigorous theoretical analysis (Grubic and Fan 2010). In this context, activity theory has been proposed as a theoretical framework for guiding conceptualization to inform the development of ontologies (Karanasios et al 2013;Thakker et al 2017).…”

OMDP: An ontology-based model for diagnosis and treatment of diabetes patients in remote healthcare systems

“…Ontology is an organized system designed to categorize and help explain the relationships between various entities in the same area of knowledge and research. 15 There are several applications of ontology-based systems including neural systems, 16 cultural variations in interpersonal communication, 17 information retrieval for mobile learning resources, 18 diabetes, 19 epilepsy, 20 and others.…”