The utilization of traditional social survey data to address today's bullying problems presents some limitations. In response, a new method to investigate and subsequently intervene is warranted. Therefore, this study analyzed big data generated by social media to identify Future Signals of bullying. This approach may contribute to effectively clarifying the problem and suggesting targeted interventions to address the bullying phenomenon in South Korea. For social big data analysis, 350,314 web documents were collected per hour each day from January 1, 2013 to June 30, 2017, from 279 subject channels based on an ontology of bullying-related topics. Term frequency, document frequency, degree of visibility, and degree of diffusion were computed to identify Future Signals. A substantial overlap of findings between studies based on social big data and traditional survey results was observed for family (e.g., parental divorce, domestic violence, child abuse), peer (e.g., transfer, friend violence), economic (e.g., economic problem), and school/academic (e.g., academic record, school control, academic stress) strain domains, whereas strains concerning the media (e. g., movie, celebrity) and cultural (e.g., materialism, hell Korea) domains seemed to be more salient in social big data. Weak Signal topics in social big data representing media and cultural strain domains (e.g., Youtube, class society, bullying culture) related to the bullying phenomenon appear to be emerging in significance. These topics and their respective strain domains represent potentially important new areas that warrant further investigation by practitioners and policymakers. These findings may allow the early detection of crucial information by providing data to support better informed insight and intervention related to the complex problem of bullying in South Korea.
All Science Journal Classification (ASJC) codes
- Computer Networks and Communications
- Electrical and Electronic Engineering