YouTube Podcast Data for Emotion Dynamics and Engagement Research

A dataset collected from YouTube podcasts and processed for research on temporal emotion dynamics and engagement prediction. It includes raw metadata and transcripts, along with processed features such as detected emotions, change points, and engagement modeling inputs. The dataset was created by anshulraj10 and was last updated on September 6, 2025.

Use Cases

• Studying emotion trajectories based on processed emotion features mentioned in the description
• Detecting emotion change points based on the change point detection features
• Predicting engagement based on the engagement modeling inputs described

Strengths

• Includes processed features like detected emotions and change points, which are ready for analysis
• Contains both raw metadata and transcripts, providing flexibility for different research approaches

Limitations

• Column-level documentation is absent; field semantics must be inferred after download
• Row count is unknown, which may limit suitability assessment
• Last updated 2025-09-06 19:44:30; freshness should be verified

Provenance

Source

YouTube podcasts

Collection Method

Collected and processed from YouTube podcasts

Freshness

Last updated 2025-09-06 19:44:30