devwithjevClassifies YouTube Comments
Jev classified 20.7k YouTube comments in 2m 27s, analyzing sentiment, emotion, intent, and spam/toxic content with confidence scores.
Slava S.@slvDev𝕏
Jev by @typesafeai in action! 20.7k YouTube comments classified in 2m 27s for just $0.20 - p50 319ms, p95 556ms per comment - 140 comments/sec - sentiment + emotion + intent + spam/toxic, each with confidence mostly Apple WWDC videos and results are kinda funny: 43% negative #1 intent is criticism (5.1k) my classification rules are probably not ideal... but you can tweak them and rerun the whole b
The comments were mostly from Apple WWDC videos. The results showed 43% negative sentiment, with criticism the top intent at 5.1k comments. The author noted that the classification rules could be tweaked and rerun.
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