CBS News Articles from 2023

News articles published by CBS News during the 2023 calendar year. The dataset contains text content from a major U.S. broadcast news network. The collection covers events and reporting from that specific year.

Use Cases

• Analyze article headlines and body text for sentiment trends across 2023.
• Train a topic model on article content to identify major news themes for the year.
• Extract named entities like persons, organizations, and locations from news text for event tracking.
• Study the linguistic style and framing of a major broadcast news outlet.
• Use article publication dates to analyze the frequency and timing of news coverage on specific subjects.

Strengths

• Content from a major, established U.S. news network.
• Focus on a single, defined calendar year (2023).

Limitations

• The exact number of articles, row count, and specific columns are unknown.
• Potential geographic bias towards U.S.-centric news coverage.
• Lack of metadata (e.g., author, section, word count) limits granular analysis.

Provenance

Source

CBS News

Collection Method

Presumably scraped or aggregated from the CBS News website or feeds.

Time Range

2023

Freshness

Covers the year 2023; update frequency is null.

Geography

Primarily United States, with potential for international coverage.