Abstract
BackgroundSocial networking services (SNSs) contain abundant information about the feelings, thoughts, interests, and patterns of behavior of adolescents that can be obtained by analyzing SNS postings. An ontology that expresses the shared concepts and their relationships in a specific field could be used as a semantic framework for social media data analytics.ObjectiveThe aim of this study was to refine an adolescent depression ontology and terminology as a framework for analyzing social media data and to evaluate description logics between classes and the applicability of this ontology to sentiment analysis.MethodsThe domain and scope of the ontology were defined using competency questions. The concepts constituting the ontology and terminology were collected from clinical practice guidelines, the literature, and social media postings on adolescent depression. Class concepts, their hierarchy, and the relationships among class concepts were defined. An internal structure of the ontology was designed using the entity-attribute-value (EAV) triplet data model, and superclasses of the ontology were aligned with the upper ontology. Description logics between classes were evaluated by mapping concepts extracted from the answers to frequently asked questions (FAQs) onto the ontology concepts derived from description logic queries. The applicability of the ontology was validated by examining the representability of 1358 sentiment phrases using the ontology EAV model and conducting sentiment analyses of social media data using ontology class concepts.ResultsWe developed an adolescent depression ontology that comprised 443 classes and 60 relationships among the classes; the terminology comprised 1682 synonyms of the 443 classes. In the description logics test, no error in relationships between classes was found, and about 89% (55/62) of the concepts cited in the answers to FAQs mapped onto the ontology class. Regarding applicability, the EAV triplet models of the ontology class represented about 91.4% of the sentiment phrases included in the sentiment dictionary. In the sentiment analyses, “academic stresses” and “suicide” contributed negatively to the sentiment of adolescent depression.ConclusionsThe ontology and terminology developed in this study provide a semantic foundation for analyzing social media data on adolescent depression. To be useful in social media data analysis, the ontology, especially the terminology, needs to be updated constantly to reflect rapidly changing terms used by adolescents in social media postings. In addition, more attributes and value sets reflecting depression-related sentiments should be added to the ontology.
Highlights
Suicide rates in Switzerland are in the middle range compared to other European countries: 1034 persons died by suicide in Switzerland in 2011.Switzerland has a federal structure, with the Swiss Federal Office of Public Health taking care of overarching issues such as health insurance and health information
It is envisaged that this report will be a key resource for those engaged in suicide prevention efforts, including first and foremost ministries of health, planners and policy-makers, and nongovernmental organizations (NGOs), researchers, health and community workers, the media and the general public
Among the 172 Member States with populations of over 300 000, the 2000−2012 change in age-standardized suicide rates ranged from a decline of 69% to an increase of 270%. Among these 172 countries, 85 (49.4%) experienced a drop in age-standardized suicide rates of over 10%, 29 (16.9%) experienced an increase of over 10%, and 58 (33.7%) had relatively small changes in age-standardized suicide rates over the 12-year period
Summary
Suicide rates in Switzerland are in the middle range compared to other European countries: 1034 persons died by suicide in Switzerland in 2011.Switzerland has a federal structure, with the Swiss Federal Office of Public Health taking care of overarching issues such as health insurance and health information.
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