Hyperpartisan News Detection Dataset

A dataset for detecting hyperpartisan news articles, created by pietrolesci. It was last updated on September 25, 2023. The specific source, size, and annotation methodology are not detailed in the available metadata.

Use Cases

• Train a binary classifier to identify hyperpartisan news articles based on textual content.
• Analyze linguistic patterns associated with political bias in media reporting.
• Benchmark the performance of different NLP models on a political bias detection task.
• Study the relationship between article framing and perceived partisanship.

Strengths

• Dataset is hosted on a major platform (huggingface) with a specific creator (pietrolesci).
• Has a clear, focused purpose for detecting hyperpartisan news.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

huggingface

Freshness

Last updated 2023-09-25 14:32:27; freshness should be verified.