From risk factors to detection and intervention: a practical proposal for future work on cyberbullying

While there is an increasing flow of media stories reporting cases of cyberbullying, particularly within
online social media, research efforts in the academic community are scattered over different topics
across the social science and computer science academic disciplines. In this work, we explored
research pertaining to cyberbullying, conducted across disciplines. We mainly sought to
understand scholarly activity on intelligence techniques for the detection of cyberbullying when it
occurs. Our findings suggest that the vast majority of academic contributions on cyberbullying
focus on understanding the phenomenon, risk factors, and threats, with the prospect of
suggesting possible protection strategies. There is less work on intelligence techniques for the
detection of cyberbullying when it occurs, while currently deployed algorithms seem to detect
the problem only up to some degree of success. The article summarises the current trends aiming
to encourage discussion and research with a new scope; we call for more research tackling the
problem by leveraging statistical models and computational mechanisms geared to detect,
intervene, and prevent cyberbullying. Coupling intelligence techniques with specific web
technology problems can help combat this social menace. We argue that a multidisciplinary
approach is needed, with expertise from human–computer interaction, psychology, computer
science, and sociology, for current challenges to be addressed and significant progress to be made.