The Online Behaviour of the Algerian Abusers in Social Media Networks
This work addresses the problem of detecting abusive content in informal, unstructured texts for Algerian social media users, but it is incremental as it focuses on a specific community without introducing new methods.
The paper conducted a statistical study on cyber-bullying and abusive content in social media, specifically analyzing the online behavior of abusers in the Algerian community using data from 200 Facebook users to aid automatic abuse detection systems.
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.