Sentiment Analysis

Analyze text to identify sentiment as negative, neutral, or positive using natural language processing.

Identifying sentiment expressed in text whether they’re negative, neutral, or positive.

Group
Negative
Neutral
Positive

Identifying sentiment expressed in text

POST https://api.aigen.online/ainlp/sentiment/v1

Request Body

Name	Type	Description
text*	String

200: OK Successful response

{
  "group_count": 1,
  "group_detail": [
    {
      "group_name": "Positive",
      "rank": 1,
      "score": 0.82
    }
  ],
  "status": "success"
}

400: Bad Request

{
  "status": "fail"
}

Example code

Python

import requests
import json

api = "https://api.aigen.online/ainlp/sentiment/v1"
headers = {"x-aigen-key": "<key>", "content-type": "application/json"}
data = json.dumps({"text": "ai สามารถช่วยแก้ปัญหาต่าง ๆ ได้"})

res = requests.post(api, data=data, headers=headers)
print(res.json())

Nodejs

const axios = require("axios");

const api = "https://api.aigen.online/ainlp/sentiment/v1";
const headers = {
  "x-aigen-key": "<key>",
};
const data = { text: "ai สามารถช่วยแก้ปัญหาต่าง ๆ ได้" };

axios
  .post(api, data, { headers: headers })
  .then((res) => {
    console.log(res.data);
  })
  .catch((err) => {
    console.error(err.response.data);
  });

PHP

<?php

$curl = curl_init();

curl_setopt_array($curl, array(
  CURLOPT_URL => 'https://api.aigen.online/ainlp/sentiment/v1',
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_CUSTOMREQUEST => 'POST',
  CURLOPT_POSTFIELDS => json_encode([
    'text' => 'ai สามารถช่วยแก้ปัญหาต่าง ๆ ได้'
  ]),
  CURLOPT_HTTPHEADER => array(
    'X-AIGEN-KEY: <aigen-key>',
    'Content-Type: application/json'
  ),
));

$response = curl_exec($curl);

curl_close($curl);
echo $response;
?>

cURL

curl --location 'https://api.aigen.online/ainlp/sentiment/v1' \
--header 'X-AIGEN-KEY: <aigen-key>' \
--header 'Content-Type: application/json' \
--data '{
  "text": "ai สามารถช่วยแก้ปัญหาต่าง ๆ ได้"
}'