YouTube Live Chat Sentiment During the 2024 U.S. Presidential Debate

221.9 MB of multimodal data from Sungwon Jung's 2026 study of emotional contagion in a YouTube live chat during a major political event. The collection includes CSV and JSONL files alongside analysis code in IPYNB and RMD formats. It was published under a CC-BY-4.0 license on figshare.

Use Cases

• Analyze real-time emotional contagion patterns based on live chat text data.
• Train multimodal sentiment analysis models based on the described text and potentially linked visual data.
• Study the dynamics of affective publics during televised political debates.
• Benchmark methods for extracting sentiment from unstructured social media streams.

Strengths

• Dataset size is 221.9 MB, indicating a substantial collection of chat data and analysis artifacts.
• Includes both raw data (CSV, JSONL) and reproducible analysis code (IPYNB, RMD, HTML).
• Released under a permissive CC-BY-4.0 license for open reuse.

Limitations

• Row count and specific column definitions are unknown, limiting initial suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Data may reflect temporal and platform bias inherent to a single YouTube live chat event.

Provenance

Source

figshare, authored by Sungwon Jung.

Collection Method

Likely collected via YouTube API from the live chat of a specific event.

Time Range

Covers the 2024 U.S. Presidential Debate.

Freshness

Last updated 2026-04-11 17:59:10