Towards understanding cyberbullying behavior in a semi-anonymous social network
Homa Hosseinmardi, Amir Ghasemian, Richard Y. Han, Qin Lv, Shivakant Mishra · 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014) · 2014
Cyberbullying has emerged as an important and growing social problem, wherein people use online social networks and mobile phones to bully victims with offensive text, images, audio and video on a 24/7 basis. This paper studies negative user behavior in the Ask.fm social network, a popular new site that has led to many cases of cyberbullying, some leading to suicidal behavior.We examine the occurrence of negative words in Ask.fm's question+answer profiles along with the social network of “likes” of questions+answers. We also examine properties of users with “cutting” behavior in this social network.