Determines the polarity of any text content: negative (neg), neutral (neu), positive (pos).
Supported Languages
Currently supporting the following languages (14): Arabic, Chinese, English, Farsi, French, German, Hungarian, Italian, Japanese, Polish, Portuguese, Romanian, Russian, Spanish.
Usage Example
This is an example of calling the Sentiment Analyzer on an English text using curl:
curl -X POST "http://localhost:8989/rest/process" -H "accept: application/json" -H "Content-Type: application/json" -d "{ \"content\": \"This phone has the worst fingerprint reader in years. It's slow, inaccurate, and brights up the entire room at night to try to use it.\", \"language\": \"eng\"}"
Calling the Sentiment Analyzer as above will generate the simple JSON response below:
{
"label": "neg",
"score": 0.7659167051315308
}
2 responses
[…] Analytics task is Classification. Document classification works for a plethora of use- cases, from sentiment/emotion analysis, intent detection, news categorization, email classification, and so on. There are few […]
[…] machines are utilized to benchmark RNN engines, such as Sentiment Analysis. The throughputs obtained for this type of engine reached 567 requests per second, equivalent to […]