Sentiment Analyzer
Commercial usage OK
579 mamodheru
Hapana watermark
Hapana kumbobvira kushanyira
Model:
+ GPT-5, Claude, Gemini
Kutenda
-
-
Polarity
-
-100 kusvika +100
Kuvimba
-
-
Summary
_Zvitsva
Chikamu
Tokens iri kubuda.
Kuwana zvakawanda Tokens
❤️ Kuda Free.ai? Tinya pano kuti utore screenshot.
Register to get a referral link and earn 30,000 tokens per friend.
Unoda zvakawanda?
Sign up free: 30,000 tokens/day
Sign Up Free
Kuongorora yako request...
Analyze text pfungwa nemahara AI. Detect zvakanaka, zvakaipa, uye neutral tones.
Maitiro ekuisa Sentiment Analyzer
1
Sarudza yako input
Tinya tebhu, wedzera faira, kana kuti nyora zvaunoda. Hapana account yaunoda.
2
Tinya kuumba
Our AI inogadzirisa yako mibvunzo mumasekondi nekushandisa yakanakisa open-source mamodheru.
3
Dhawunirodha & shandisa
Dhawunirodha, kopa kana kugovera yako mhinduro. Yemahara yekushandisa personally uye commercially.
Usashandisa iyi chirongwa kuburikidza neAPI
Automatize iyi chirongwa kubva yako pachako code. OpenAI-inowirirana REST endpoint, Bearer-token auth, hapana zvishoma SDK zvinoda. Token mari inoenzana web interface.
curl -X POST https://api.free.ai/v1/chat/ \
-H "Authorization: Bearer sk-free-..." \
-H "Content-Type: application/json" \
-d '{"model": "qwen7b", "messages": [{"role": "user", "content": "Summarize this: ..."}]}'Kubatana Free AI Zvirongwa
Sentiment Analyzer - FAQ
Zvimwe zvinhu zvina, zvichienderana nenzira yawakasarudza: (1) kuomarara kwese - -100 kusvika +100 score nechokwadi; (2) 6-dimensional emotions - rusununguko, kunzwa, kurwadziwa, kusafara, kushamisika, kushungurudzika; (3) kuomarara kwese - kubvisa zvakanyorwa zvimiro kana zvikamu uye kutamba zvidimbu zvakasiyana; (4) sarcasm / subtext - kuchinja polarity yepasi peiyo irony yakaonekwa; (5) per-sentence - tags every sentence individually. Choose the mode that matches your use case.
Yeah - a typical 200-word review runs the default Qwen 3 30B model at ~200 tokens, comfortably inside the 6,000 anonymous or 30,000 signed-up daily pool. Forensic-deep aspect analysis on longer texts costs ~600 tokens. No sign-up required to try a few.
Kuenzanisa pamusoro zvose polarity (~ 85% mubatanidzwa nevanhu raters pa clear-cut text), pamberi Google pamusoro nyaya-kuumbwa chokwadi, pamberi pane zvakawanda pamusoro sarcasm nekuti isu tinopa chimiro zvakajeka sarcasm-detection zvinodiwa. Enterprise vatengesi kubhadharisa $ 1-4 pa 1,000 zviuru. Our advantage: emotion radar + aspect-based output in one call, free, no API key to provision.
Yeah - chinja kune "Sarcasm + subtext" mode. Iyo system prompt inotiudza kuti tiite sei kuti tiite kuti pfungwa iite sekuti iri mumifananidzo kana kuti iri mumifananidzo. (Oh great, another delay" scores negative despite positive-word presence). Kunyatsonzwisisa kwechiratidzo chekutaura chinoratidza sarcasm ndekwe ~80%; chiratidzo chekutaura chinoratidza pasive-aggression icho chine matambudziko. The "Mixed" verdict + low-confidence score is your flag to read the text yourself.
Instead of one verdict for the whole text, you get separate scores for each entity or feature mentioned. Example: "The hotel was beautiful but the breakfast was cold and the wifi was terrible" yields {hotel: +80, breakfast: -50, wifi: -70}. Ideal for product reviews, restaurant feedback, and NPS comments where customers mix praise and complaints in one paragraph.
99 languages. The six emotion dimensions come from Ekman basic-emotion research and translate universally. Accuracy is highest on English, Spanish, French, Portuguese, German, Chinese, Japanese; lower-resource languages work but can produce slightly lower confidence scores.
Yeah - iyo ndiyo imwe yeakanyanya kukosha ekushandisa zviitiko. Kufamba zvitupa zvinosvika kuburikidza ne "Support ticket" domain mode; zvitupa zvinotora pasi pe -50 polarity neyakakwira kurwadziwa-dimension kuenda kune yako senior support queue, yakajeka-kuvimbika zvitupa nzira kune self-service. Export JSON kuburikidza nekudzvanya kurodha pasi uye waya mu Zendesk / Freshdesk automations.
Yeah - POST to /v1/chat/ with the same system prompt this page builds (inspect source for the exact prompt). Returns structured JSON. Good for dashboards that ingest thousands of reviews nightly. Bearer auth, monthly limits. Docs at /api/.
Kutenda kunoratidzwa ne model' s certainty, kwete yako certainty. Short inputs (< 20 words), ambiguous text, and mixed- polarity content score low. A low- confidence positive is not a confident negative - it is "I don' t know". Treat any score below 50 as needing human review.
UI inofamba imwe nyaya panguva imwe. For bulk, the JSON+CSV download lets you wire the API into a Python or Node script that iterates your dataset. Limits: 20,000 characters per call, 100 calls/hour per IP for anonymous users, 1,000/hour for signed-up accounts. Enterprise rate limits available - contact us.
Lexalytics uye Repustate kubhadharisa $ 500-5,000 / mo yechiyero chinoenderana neaspect-based + emotional detection. Our tool is free for most workflows; premium models (GPT-5, Claude Sonnet) available per-call for the highest-stakes use cases like earnings-call transcripts.
Mazita anogadziriswa mupfungwa paGPU yedu, asi haasi kuchengetwa padhiski kune vashandisi vasingazivikanwe. Vashandisi vakanyoresa vanoona ongororo mudashboard yavo kwemazuva 7. Hatina kugovera mazita nevamwe kana kushandisa izvi kudzidzisa. Kuti uwane zero-log kutevedzera, shandisa yako yese API-key-gated endpoint - taura nesu nezve SLAs yekambani.
Ungaitei kuti uite izvi?