YouTube × Engagement

5 datasets that are both from YouTube and tagged Engagement.

5 datasets.

YTCommentVerse: Multi-Category YouTube Comment Corpus Analyzed

A YouTube (multi-category comment corpus) dataset of 40,824,926 comments from 20,568,637 unique commenters across 178,027 videos, collected by YTCommentVerse project team via YouTube Data API. Each record contains hashed video ID, hashed commenter channel ID, comment text, vote count, video category (entertainment/gaming/news/music/etc.). YTCommentVerse contains 40,824,926 YouTube comments spanning 25 categories with privacy-preserving hashed identifiers, enabling large-scale multilingual comment analysis. Suitable for YouTube comment analysis, multilingual NLP, engagement research, content moderation, commenter behavior modeling, cross-category platform analysis.

40.8M records20.7M nodes40.8M edges2025

YouTube Social Network Growth Analyzed

A YouTube (user social network growth over time) dataset of 3,223,585 nodes and 9,375,374 edges, collected by A. Mislove et al. via YouTube API. Each record contains directed: False, weighted: True, temporal: True. Temporal undirected YouTube friendship network showing how the social graph grew over time — 9.4M edges with Unix timestamps.. Suitable for temporal network analysis, social network growth modeling, YouTube social dynamics.

3.2M records3.2M nodes9.4M edges2009

Wish 107.5 YouTube Comments Dataset Analyzed

A YouTube dataset of 2,004,605 comments from 635 videos, collected by Bwan Wando via YouTube API. Each record contains comment text, like count, reply count, video ID, timestamp, anonymized author ID. A large-scale dataset of 2M+ comments from the Wish 107.5 YouTube channel, a popular Philippine FM radio station known for its live music performances. Suitable for sentiment analysis, topic modeling, fan engagement, cultural studies, natural language processing.

2M records2024

YouTube Shorts Dataset: 100,000+ Short-Form Videos Analyzed

A YouTube Shorts dataset of 68,699 short-form video records (metadata only), collected by JamilAL01 via the YouTube Data API (GitHub, 2025). Each record contains video title, description, tags, channel info, category, and engagement metrics (views, likes, comments, duration). metadata-only corpus with no video files — purely textual and categorical fields enabling content and engagement analysis without requiring video storage or processing. Suitable for short-form video trend analysis, content categorization, engagement prediction, and creator behavior modeling.

68.7K records2025

YouTube Travel Videos Metadata Index Analyzed

A YouTube (Travel Videos Metadata Index) dataset of 2,267 travel-related YouTube video records, collected by Samuel & Audrey Media Network via YouTube API (2026). Each record contains video titles, descriptions, region tags, topic tags, view counts, publication years, and validity flags. The dataset is notable for its metadata-only index designed for travel video archive search, regional coverage analysis, and linking video records with transcript datasets and destination research. Intended for research into tourism communication research, creator-media analysis, regional coverage analysis, and retrieval workflows across travel videos, transcripts, and article corpora.

2.3K records2026