BGMI Live-Chat Sentiment: 7.97M Hinglish Esports Messages

7.97 million live-chat messages from YouTube broadcasts of the BGMI esports scene, annotated with gold-standard sentiment labels. The data captures audience reactions in Hinglish, a blend of Hindi and English. The dataset's origin, author, and specific collection period are not detailed in the available metadata.

Use Cases

• Train sentiment classifiers for Hinglish text based on the provided gold labels.
• Analyze real-time audience engagement and emotional trends during esports broadcasts.
• Study code-switching patterns between Hindi and English in informal digital communication.
• Benchmark multilingual NLP models on a large-scale, domain-specific live-chat corpus.

Strengths

• Contains 7.97 million data points, providing substantial scale for model training.
• Includes gold-standard sentiment labels, which are high-quality human annotations.
• Focuses on a specific, high-engagement domain (esports live-chat).

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Last update date is unknown; freshness unverified.
• Data may reflect geographic, linguistic, and platform bias inherent to its source.

Provenance

Source

YouTube live-chat streams for BGMI (Battlegrounds Mobile India) esports.

Collection Method

Likely scraped and annotated from public YouTube streams.