Analyzing labeled cyberbullying incidents on the instagram social network

Abstract

Cyberbullying is a growing problem affecting more than half of all American teens. The main goal of this paper is to study labeled cyberbullying incidents in the Instagram social network. In this work, we have collected a sample data set consisting of Instagram images and their associated comments. We then designed a labeling study and employed human contributors at the crowd-sourced CrowdFlower website to label these media sessions for cyberbullying. A detailed analysis of the labeled data is then presented, including a study of relationships between cyberbullying and a host of features such as cyberaggression, profanity, social graph features, temporal commenting behavior, linguistic content, and image content.