KidsTube: Detection, Characterization and Analysis of Child Unsafe Content & Promoters on YouTube

TL;DR

This paper presents methods to detect and analyze unsafe content and promoters targeting children on YouTube, achieving high accuracy and revealing community structures that facilitate unsafe content exposure.

Contribution

It introduces a combined supervised and CNN-based approach for detecting unsafe child content and characterizes the behavior and community structure of unsafe content promoters.

Findings

Detection accuracy of 85.7% achieved

Unsafe promoters are less popular and less engaged

Unsafe content is closely clustered with safe content

Abstract

YouTube draws large number of users who contribute actively by uploading videos or commenting on existing videos. However, being a crowd sourced and large content pushed onto it, there is limited control over the content. This makes malicious users push content (videos and comments) which is inappropriate (unsafe), particularly when such content is placed around cartoon videos which are typically watched by kids. In this paper, we focus on presence of unsafe content for children and users who promote it. For detection of child unsafe content and its promoters, we perform two approaches, one based on supervised classification which uses an extensive set of video-level, user-level and comment-level features and another based Convolutional Neural Network using video frames. Detection accuracy of 85.7% is achieved which can be leveraged to build a system to provide a safe YouTube experience for kids. Through detailed characterization studies, we are able to successfully conclude that unsafe content promoters are less popular and engage less as compared with other users. Finally, using a network of unsafe content promoters and other users based on their engagements (likes, subscription and playlist addition) and other factors, we find that unsafe content is present very close to safe content and unsafe content promoters form very close knit communities with other users, thereby further increasing the likelihood of a child getting getting exposed to unsafe content.