Area:
Industrial Psychology, Social Psychology, Management Business Administration
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High-probability grants
According to our matching algorithm, Robin Kowalski is the likely recipient of the following grants.
| Years |
Recipients |
Code |
Title / Keywords |
Matching
score |
| 2015 — 2017 |
Hu, Hongxin
Luo, Feng
Mazer, Joseph
Kowalski, Robin |
N/AActivity Code Description:
No activity code was retrieved: click on the grant title for more information |
Eager: Defending Against Visual Cyberbullying Attacks in Emerging Mobile Social Networks
Adolescents have fully embraced social networks for socializing and communicating. However, cyberbullying has become widely recognized as a serious social problem, especially for adolescents using social networks. Also, cyberbullying techniques change rapidly. Perpetrators can use the camera-capacity of their mobile devices to bully others through making and distributing harmful pictures or videos of their victims via mobile social networks. While the social and psychological aspects of cyberbullying have been the subject of intense study, little research has been dedicated to tracing cyberbullying attacks accurately and automatically using computing technologies. Indeed, the development of automatic cyberbullying detection techniques is still in the nascent stages. All state-of-the-art studies in automatic cyberbullying detection have mainly focused on the content of the text written by the perpetrators of cyberbullying (a.k.a. textual cyberbullying), while largely overlooking the misuse of visual media in cyberbullying. This research reveals that there are great challenges that must urgently be resolved to ensure the most robust defense against visual cyberbullying attacks.
This project is designing and developing a systematic solution for automatic detection of and intervention in visual cyberbullying attacks in emerging mobile social networks. The researchers are identifying new person and situational factors associated with visual cyberbullying and designing a cross-feature classifier for automatic visual cyberbullying detection. The project is also building an adaptive cyberbullying intervention system to continuously monitor situation changes in cyberbullying and provide specific response strategies for each associated participant. The proposed methods can be potentially adopted and implemented in popular mobile social network platforms to prevent visual cyberbullying. The system designed by this project could be used to curb the rising trend in instances of cyberbullying among young people and reducing the myriad harmful effects that follow from it. In addition, since many other common cyber threats targeting adolescents must also deal with visual media now, the fundamental results generated by this project could be expanded to cope with those threats beyond cyberbullying.
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