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YouTube Engagement and Trends Data
Social Media and Posts
Tags and Keywords
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About
A rich collection of metadata from over 2,000 YouTube videos is provided, offering a unique opportunity to explore content performance on the platform. With detailed information on video titles, views, likes, tags, and publication dates, this data allows for a deep dive into digital content trends. It is ideal for understanding the factors that drive audience engagement and video popularity.
Columns
- video_id: A unique identifier for each YouTube video.
- title: The title of the video, which is useful for NLP and sentiment analysis.
- description: The text description accompanying the video, which may contain links or keywords.
- published_date: The date the video was published.
- channel_id: The unique identifier for the YouTube channel.
- channel_title: The name of the channel that published the video.
- tags: Keywords associated with the video, often separated by commas.
- category_id: A numerical ID representing the video’s category (e.g., music, gaming).
- view_count: The total number of times the video has been viewed.
- like_count: The total number of likes the video has received.
- comment_count: The total number of comments on the video.
- duration: The length of the video.
- thumbnail: The URL for the video's thumbnail image.
Distribution
The data is provided in a single CSV file named
youtube_data.csv, with a size of approximately 799.63 kB. It is structured into 13 columns and contains 600 rows of data.Usage
This dataset is well-suited for a variety of analytical tasks, including:
- Predicting video popularity using features like titles and tags.
- Conducting Natural Language Processing (NLP) on video titles and descriptions.
- Analysing trends in content types versus audience engagement.
- Developing time-series forecasts for views, likes, and comments.
- Building clustering algorithms or recommendation systems for video categorisation.
Coverage
The dataset contains metadata for a wide range of YouTube videos without specific geographical, temporal, or demographic limitations mentioned. The data includes videos with various publication dates and from numerous channels.
License
CC BY-SA 4.0
Who Can Use It
- Data Analysts: Can perform trend analysis to identify patterns in video performance and audience engagement.
- Machine Learning Enthusiasts: Can build predictive models for video popularity or develop recommendation systems.
- Content Creators: Can gain insights into what makes content successful and optimise their titling, tagging, and description strategies.
Dataset Name Suggestions
- YouTube Video Performance Analytics
- YouTube Engagement and Trends Data
- Viral Video Metrics Dataset
- YouTube Content Performance Metrics
Attributes
Original Data Source: YouTube Engagement and Trends Data
QUALITY