Sentiment & emotion analysis
Know which fires are burning hottest
Filters mentions by negative sentiment, so your team sees what matters, and goes a layer deeper with emotion detection, flagging angry and frustrated posts so the most volatile ones get handled first. It even catches sarcasm, so “great job, as always 🙄” doesn’t slip through as praise.
And sentiment is read per brand, not per post: “Singapore Airlines was incredible. Lufthansa, never again” counts as positive for one and negative for the other, where most tools would call it neutral.
- Per-keyword sentiment; no more misread “mixed” mentions
- Emotion detection: anger, frustration, fear, joy, and even sarcasm
- 96% accuracy across 100+ languages, with auto-translation