Semantic MOCIBA 2021: A Vocabulary for Cyberbullying based on Open Data Analysis

Abstract

The Information and Communication Technologies are present in homes, cultural, work and academic environments to improve quality of life, however, they are also means for harassment or cyberbullying, a form of violence that affects the mental and physical health of internet users. Annually, staff of the National Institute of Statistics and Geography conducts interviews to collect anonymous data on the prevalence of cyberbullying via a survey called MOCIBA. Until now, the six applications of this survey have had a distinct thematic coverage and questionnaire, as a consequence, heterogeneos open datasets for results are produced making analysis over time difficult. This paper presents Semantic MOCIBA 2021, an original ontology and vocabulary dedicated to the exploitation of MOCIBA 2021 dataset. The goal is to significantly improve data reuse by providing a standardized vocabulary using Semantic Web technologies and ontologies. The paper describes the development process of this vocabulary from scratch to form enriched datasets where concepts and relationships are formalized to represent and reason via linked data. The Semantic MOCIBA 2021 vocabulary can serve as a reference resource and practical tool for students and practitioners for information systems communities and to support the decision-making process and the generation of actions against cyberbullying by individuals or organizations in the academic or social sector based on the evidence distributed as open data.