Towards Understanding Cyberbullying Behavior in a Semi-Anonymous Social Network

TL;DR

This paper investigates cyberbullying in Ask.fm by analyzing negative language and social interactions, revealing patterns associated with harmful behaviors and providing insights into the social dynamics of semi-anonymous online environments.

Contribution

It introduces a novel analysis of cyberbullying behavior in Ask.fm, combining linguistic and social network data to understand negative user interactions.

Findings

Negative words correlate with reports of harmful behavior.

Users with self-harm tendencies show distinct social patterns.

Social network analysis reveals clusters of cyberbullying activity.

Abstract

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 247 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.fms 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.