  Connecting to social media networks becomes a daily task for the majority of
people around the world, and the amount of shared information is growing
exponentially. Thus, controlling the way in which people communicate is
necessary, in order to protect them from disorientation, conflicts,
aggressions, etc. In this paper, we conduct a statistical study on the
cyber-bullying and the abusive content in social media (i.e. Facebook), where
we try to spot the online behaviour of the abusers in the Algerian community.
More specifically, we have involved 200 Facebook users from different regions
among 600 to carry out this study. The aim of this investigation is to aid
automatic systems of abuse detection to take decision by incorporating the
online activity. Abuse detection systems require a large amount of data to
perform better on such kind of texts (i.e. unstructured and informal texts),
and this is due to the lack of standard orthography, where there are various
Algerian dialects and languages spoken.
