Labelled headlines and True/False scores for US-Iran Headlines. The dataset is hosted on Kaggle and is tagged for topics including International Relations and News. The author, organization, and specific data scale are not provided.
Use Cases
- Train a binary classifier to verify news headlines based on the provided True/False labels.
- Analyze media sentiment and framing in US-Iran conflict reporting based on headline text.
- Study patterns of misinformation or bias in news headlines related to international relations.
Strengths
- Data is explicitly labelled with True/False scores, providing a clear target for classification tasks.
- The dataset focuses on a specific geopolitical conflict, offering domain-specific text data.
Limitations
- Row count, file formats, and column-level documentation are unknown, which limits suitability assessment.
- The last update date is unknown; freshness is unverified.
- Data may reflect temporal or source bias inherent to the news headlines collected.
Provenance
- Source
- Kaggle
- Collection Method
- Headlines were likely gathered from news sources and manually or automatically labelled.
- Geography
- Focus on US-Iran relations, but specific geographic coverage of sources is unknown.