YTLive: A Dataset of Real-World YouTube Live Streaming Sessions

TL;DR

YTLive is a comprehensive, publicly available dataset capturing real-time viewer behavior during YouTube Live streams, enabling research on streaming patterns, viewer engagement, and system optimization.

Contribution

The paper introduces YTLive, the first large-scale, publicly accessible dataset of YouTube Live streaming sessions with detailed viewer metrics and initial analysis.

Findings

Viewer counts are higher and more stable on weekends.

Shorter streams attract larger, more consistent audiences.

Longer streams grow slowly with greater variability.

Abstract

Live streaming plays a major role in today's digital platforms, supporting entertainment, education, social media, etc. However, research in this field is limited by the lack of large, publicly available datasets that capture real-time viewer behavior at scale. To address this gap, we introduce YTLive, a public dataset focused on YouTube Live. Collected through the YouTube Researcher Program over May and June 2024, YTLive includes more than 507000 records from 12156 live streams, tracking concurrent viewer counts at five-minute intervals along with precise broadcast durations. We describe the dataset design and collection process and present an initial analysis of temporal viewing patterns. Results show that viewer counts are higher and more stable on weekends, especially during afternoon hours. Shorter streams attract larger and more consistent audiences, while longer streams tend to grow slowly and exhibit greater variability. These insights have direct implications for adaptive streaming, resource allocation, and Quality of Experience (QoE) modeling. YTLive offers a timely, open resource to support reproducible research and system-level innovation in live streaming. The dataset is publicly available at github.