Harassment by cyberbullies is a significant phenomenon on the social media. Existing works for cyberbullying detection have at least one of the following three bottlenecks. First, they target only one particular social media platform (SMP). Second, they address just one topic of cyberbullying. Third, they rely on carefully handcrafted features of the data. We show that deep learning based model...

Online social networks brought a new definition to relationships and communications. One may have hundreds of friends in cyberspace without even having seen their real faces. Along with this transition there is increasing evidence that bullying has transformed as well, from school yards to internet precincts – cyberbullying. Although bullying draws a lot of attention, due to its technical aspec...

Friendships, relationships and social communications have all gone to a new level with new definitions as a result of the invention of online social networks. Meanwhile, alongside this transition there is increasing evidence that online social applications have been used by children and adolescents for bullying. State-of-the-art studies in cyberbullying detection have mainly focused on the cont...

Cyberbullying is a phenomenon which negatively affects the individuals, the victims suffer from various mental issues, ranging from depression, loneliness, anxiety to low self-esteem. In parallel with the pervasive use of social media, cyberbullying is becoming more and more prevalent. Traditional mechanisms to fight against cyberbullying include the use of standards and guidelines, human moder...

While social media offer great communication opportunities, they also increase the vulnerability of young people to threatening situations online. Recent studies report that cyberbullying constitutes a growing problem among youngsters. Successful prevention depends on the adequate detection of potentially harmful messages and the information overload on the Web requires intelligent systems to i...

With the vast number of comments posted daily on social media and other platforms, manually monitoring internet activity for possible national security risks or cyberbullying is an impossible task. However, with recent advances in machine learning (ML), automatic such posts becomes feasible. There still issue privacy internet; however, this study, only technical aspects designing automated syst...

The automatic monitoring of cyberbullying on social networking sites has potential for signalling harmful messages, preventing these messages from remaining online and providing timely responses. Although technological advancements are made to optimise automatic cyberbullying detection systems, little is known about its desirability and requirements. Experts in the field of cyberbullying, as ex...

Cyberbullying is becoming a major concern in online environments with troubling consequences. However, most of the technical studies have focused on the detection of cyberbullying through identifying harassing comments rather than preventing the incidents by detecting the bullies. In this work we study the automatic detection of bully users on YouTube. We compare three types of automatic detect...