Developing a Human Affective States and their Influences Ontology

The study of human affective states and their influences has been a research interest in psychology, and is also becoming more and more a field of interest in computer science. The affective computing paradigm allows us to use theories and findings from psychology in the development of human affective applications. However, because of the complexity of human affect, there is a danger of misunderstanding the concepts shared via human or computer communication. We address this matter by using the notion of an Ontology from the Semantic Web field to develop a Human Affective States Ontology (HASO). Our ontology represents the knowledge that is necessary to model affective states and their influencing factors in a computerized format. In this work, we present the development and modularization of HASO, and we provide the results obtained during its evaluation:

  1. Human Affective States Ontology (HASO):    The Human Affective States Ontology (HASO) has been developed in the OWL language. It provides knowledge and a common vocabulary regarding human affective states (emotion, mood, sentiment), in a machine-accessible or machine-readable format. Nowadays, humans and computer applications often need to communicate and share knowledge. However, everyone expresses themselves in his or her own language, with different terms and meanings. Ontologies aim to unify the terms and meanings in order to enable effective communication between people and computers. Ontologies capture the domain knowledge and provide an approved understanding of the domain. The study of human emotion, mood, and sentiment is significant as these concepts have an impact on human behavior. Building an ontology for this domain allows us to then build a semantic application.
    1.  HASO (download Ontology from here: Proposed Ontology Human Affective States HASO covers a wide range of human affective states and therefore many topics. Through modularization, we create modules that handle parts of the ontology.
    2. Ontology modularization (download here: Proposed Ontology Human Affective States HASO Modularization) aids in scalability, reusability, and validation process.


  1. HASIO Question Answering system (HASIOQA) is a system that aims to overcome the complexity and difficulty of SPARQL Query by using natural language user interface. The system receives as input a question expressed in English and then convert the question to SPARQL query to retrieve the answer from the Human Affective States and their Influences Ontology ( HASIO). We implemented HASIOQA by using Eclipse environment and Jena Ontology API . Apache Jena is an open source Semantic Web framework for Java. It provides an API to extract data Ontology.  First, we defined regular expressions to match the natural language questions. Then we defined a parametrized SPARQL Query to run a query against HASIO through Jena based on the user natural language question. Please download HASIOQA here: (HASIO_Information_Catalogue)