Solution: Sentiment & Emotion Analysis
Words lie. Voices don't.
Text-based sentiment scoring misses what spoken content makes obvious: sarcasm, enthusiasm, hesitation, emotional weight. Gossip analyzes tone alongside words and scores emotion separately from sentiment, so your team sees what mentions actually feel like, not just what they technically say.
“Yeah... great product. Really lived up to the hype.”
How it was said
Words alone miss the meaning.
A sarcastic "yeah, great product" and a sincere "yeah, great product" use identical words. Text-based sentiment scoring treats them identically and often inverts polarity on sarcastic statements. Gossip analyzes delivery alongside the words themselves, so the score reflects what the speaker actually meant. The clearest signal in spoken media is in the voice, not the transcript.
How it was said
Words alone miss the meaning.
A sarcastic "yeah, great product" and a sincere "yeah, great product" use identical words. Text-based sentiment scoring treats them identically and often inverts polarity on sarcastic statements. Gossip analyzes delivery alongside the words themselves, so the score reflects what the speaker actually meant. The clearest signal in spoken media is in the voice, not the transcript.
Sentiment scoring
Their support team? Wow. They've really outdone themselves this time.
Words alone
Words + delivery
Heavy emphasis on "wow" and a dry delivery flip the polarity. Gossip reads the delivery alongside the words.
Beyond positive and negative
Sentiment is one dimension. Emotion is another.
A negative mention of your brand might be frustrated, dismissive, anxious, or outright angry, and each calls for a different response. Gossip distinguishes emotion from polarity, so your team sees not just that a conversation was negative but how it felt. That distinction is what separates a single grumpy reviewer from the early signal of a brewing crisis, the difference between reacting to noise and responding to something that actually matters.
Beyond positive and negative
Sentiment is one dimension. Emotion is another.
A negative mention of your brand might be frustrated, dismissive, anxious, or outright angry, and each calls for a different response. Gossip distinguishes emotion from polarity, so your team sees not just that a conversation was negative but how it felt. That distinction is what separates a single grumpy reviewer from the early signal of a brewing crisis, the difference between reacting to noise and responding to something that actually matters.
Emotion radar
Sarcasm, hedging, and irony
Real sentences are messier than dictionaries.
"Their product is fine, I guess" is hedged negative. "It works well... when it works" is conditional praise that is actually a complaint. "Wow, what a great launch" can mean exactly the opposite. Gossip's models are trained on how people actually talk, across 11 languages, so the score reflects intent, not just vocabulary. The hard cases are where text-first scoring fails most visibly. They are where Gossip's voice signal does the most work.
Sarcasm, hedging, and irony
Real sentences are messier than dictionaries.
"Their product is fine, I guess" is hedged negative. "It works well... when it works" is conditional praise that is actually a complaint. "Wow, what a great launch" can mean exactly the opposite. Gossip's models are trained on how people actually talk, across 11 languages, so the score reflects intent, not just vocabulary. The hard cases are where text-first scoring fails most visibly. They are where Gossip's voice signal does the most work.
Hard cases, scored honestly
“Their product is fine, I guess.”
Sentiment scoring
Their support team? Wow. They've really outdone themselves this time.
Words alone
Words + delivery
Heavy emphasis on "wow" and a dry delivery flip the polarity. Gossip reads the delivery alongside the words.
Emotion radar
Hard cases, scored honestly
“Their product is fine, I guess.”
The difference
Before and after.
Sentiment scored on transcript text alone, with no signal from tone or delivery.
Voice-aware scoring: pace, emphasis, and intonation read alongside the words themselves.
Sarcasm and ironic praise scored as positive, generating false confidence in your dashboards.
Sarcasm and irony correctly identified and scored against intent, not vocabulary.
A "negative" tag with no information about what kind of negative: frustration, anger, anxiety, or dismissal.
Emotion detected as a separate dimension, so your team can prioritize responses by feeling, not just polarity.
Comparative statements ("X is fine, but Y is better") collapsed into a single sentiment for the whole sentence.
Each entity in a sentence scored independently, so credit and criticism land where they actually belong.
What customers say
Real results, in their own words.
The insight is precise, sometimes brutally so. It is extremely valuable to see how we succeed (or fail) in our quest for relevant visibility.
Paal Leveraas
CEO, Tilt.works
We managed to catch a potentially damaging conversation about our products thanks to Gossip.
Kamilla Abrahamsen
Communication Manager, Tomra Systems ASA
Gossip saves us time and is informative, allowing us to pick up on developments in the political debate more quickly.
Marius Doksheim
Head of Insight, Civita
Included capabilities
See sentiment that actually listens.
We'll walk you through real mentions of brands you choose, so you can see for yourself how Gossip handles tone, sarcasm, and emotion in spoken content.
Request a demoWhat you'll get from the demo
- A side-by-side comparison: Gossip's voice-aware sentiment vs text-only sentiment on the same audio clips.
- A live emotion breakdown across mentions of a brand of your choice: frustration, enthusiasm, anxiety, dismissal.
- A sarcasm and irony walkthrough on a podcast or video clip you pick.