Sentiment

Similar to the Emotions API, this model tries to determine the general sentiment of a given text based on how it was written.

Prediction labels

Limits

The maximum length accepted is 512 characters.

Emotion	Emoji	Example
positive	➕	this was an incredible achievement
negative	➖	this wasn't an incredible achievement
neutral	🟰	this is just a text

Invokation

cURL

curl -L -G 'http://api.textkit.ai/detect/sentiment' \
    --data-urlencode 'text=yeah, man! Go!' \
    --header 'X-API-Key: your_api_key_here' 

Python

import requests

url = "https://api.textkit.ai/detect/sentiment?text=this was an incredible achievement"

payload={}
headers = {
  'X-API-Key': 'your_api_key_here'
}

response = requests.request("GET", url, headers=headers, data=payload)

print(response.text)

PHP

<?php

$curl = curl_init();

$url = "https://api.textkit.ai/detect/sentiment?text=" . urlencode("this was an incredible achievement");

curl_setopt_array($curl, array(
  CURLOPT_URL => $url,
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => '',
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 0,
  CURLOPT_FOLLOWLOCATION => true,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => 'GET',
  CURLOPT_HTTPHEADER => array(
    'X-API-Key: your_api_key_here'
  ),
));

$response = curl_exec($curl);

curl_close($curl);
echo $response;

Response

{
    "prediction": {
        "sentiment": "positive",
        "emoji": "➕"
    },
    "confidence": "0.942",
    "time_ms": 778
}

Field	Meaning
prediction	The predicted label. See above for reference
confidence	Value between 0 and 1 that indicates how confident the model is
time_ms	Time in milliseconds the model took to predict the label. It does not account for the network round trip time between request and response