News Popularity Metrics Across Social Media Platforms

News Popularity in Multiple Social Media Platforms is a dataset from the UCI Machine Learning Repository. It contains metrics for measuring the popularity and engagement of news articles across different social media platforms. The dataset's creator and specific temporal coverage are not provided.

Use Cases

• Predict total engagement score using platform-specific metrics like Facebook shares and Twitter retweets.
• Analyze correlation between multimedia content features (e.g., image count, video length) and platform-specific popularity.
• Classify high-vs-low popularity articles using features like headline sentiment and keyword density.
• Model cross-platform sharing patterns by comparing metrics like LinkedIn clicks and Reddit upvotes across article categories.

Strengths

• Data is hosted and curated by the reputable UCI Machine Learning Repository.
• Covers multiple major social media platforms for comparative analysis.
• Includes features for both content (multimedia) and engagement metrics.

Limitations

• Exact row count, column list, and data volume are unknown.
• Data may be stale or have a limited time range, as the last update date is unknown.
• Potential for class imbalance if popularity metrics are skewed towards a few viral articles.

Provenance

Source

UCI Machine Learning Repository

Collection Method

null

Time Range

null

Freshness

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Geography

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