Dark Mode
CNN YouTube Commentary and Sentiment Registry
Social Media and Posts
Tags and Keywords
Trusted By
"No reviews yet"
Free
About
Capturing the pulse of public discourse through recent CNN YouTube commentaries offers a unique view into how audiences engage with global news. By examining thousands of user comments, engagement metrics, and temporal data, analysts can identify shifting sentiments and evolving opinions in real-time. This collection provides a bridge between raw social media interactions and structured insights, allowing for a thorough exploration of the trends and patterns that define online political and social discussions.
Columns
- comment_text: The specific text entries posted by users on the CNN YouTube channel, providing the primary material for linguistic and sentiment analysis.
- likes: A numerical count representing the number of likes each comment received, serving as a key indicator of audience agreement and engagement.
- comment_time: A temporal marker indicating when the comment was posted, expressed in the number of hours prior to the data collection.
Distribution
The information is delivered in a CSV file titled
Cleaned_cnn_comments.csv with a file size of 5.01 MB. It consists of over 41,500 valid records structured across 3 distinct columns. The resource maintains high data integrity with a 100% validity rate for text and time entries, and it holds a perfect usability score of 10.00.Usage
This resource is ideal for performing sentiment analysis and natural language processing to detect public reactions to current events. Researchers can correlate the frequency of likes with specific keywords to identify high-engagement topics or use the temporal data to map how public opinion evolves over the course of a news cycle. It also serves as a robust foundation for building classification models and exploring the dynamics of digital communication.
Coverage
The geographic scope is global, reflecting the diverse international audience of the CNN YouTube channel. Temporally, the data focuses on recent activity from the past week, though the records include entries dating back as far as 7,200 hours. The demographic reach encompasses various English-speaking user groups participating in online news discussions.
License
CC0: Public Domain
Who Can Use It
Social media analysts and digital strategists can leverage these metrics to understand audience reception of specific news segments. Academic researchers studying political science or linguistics can use the commentary to examine the nature of online discourse and polarisation. Additionally, data science students can utilise the mix of text and numerical data to practice sentiment scoring and trend forecasting.
Dataset Name Suggestions
- CNN YouTube Commentary and Sentiment Registry
- Public Discourse Trends: CNN Audience Engagement
- CNN News Comments and Social Metrics Archive
- Temporal Analysis of CNN YouTube Interactions
- CNN Sentiment and Engagement Database
Attributes
Original Data Source: CNN YouTube Commentary and Sentiment Registry
QUALITYLoading...
Free
Download Dataset in ZIP Format
Recommended Datasets
Loading recommendations...