🆕 Thai Sentimental Analysis

🆕 ระบบวิเคราะห์อารมณ์ความรู้สึก

Welcome to iApp Thai Sentimental Analysis API, an AI product developed by iApp Technology Co., Ltd. Our API provides powerful sentiment analysis capabilities for Thai text, classifying emotions and opinions into positive, negative, and neutral categories with high accuracy.

Try Demo

Visit our API Portal to test the Thai Sentimental Analysis API with your own text.

Getting Started

1. Prerequisites

   • An API key from iApp Technology
   • Thai text input
   • Internet connection

2. Quick Start

   • Fast sentiment classification
   • High accuracy prediction
   • Simple REST API interface

3. Key Features

   • Three-way sentiment classification (Positive, Negative, Neutral)
   • Confidence score for predictions
   • Fast response time
   • Easy integration

4. Security & Compliance

   • GDPR and PDPA compliant
   • No data retention after processing

How to get API Key?

Please visit API Portal to view your existing API key or request a new one.

Example

Sentiment Analysis Request

    curl --location --request POST 'https://api.iapp.co.th/sentimental-analysis/predict?text=เขาเป็นคนดี ชอบช่วยเหลือผู้อื่น' \
    --header 'apikey: {YOUR API KEY}'

Sentiment Analysis Response

Positive

{
    "label": "pos",
    "score": 0.5532798171043396
}

Neutral

{
    "label": "neu",
    "score": 0.8166645169258118
}

Negative

{
    "label": "neg",
    "score": 0.9052726626396179
}

Features & Capabilities

Core Features

• Classifies Thai text into three sentiment categories: positive, negative, and neutral.
• Utilizes advanced Natural Language Processing (NLP) techniques for accurate sentiment analysis.
• Provides insights into emotions and opinions expressed in Thai text data.

Supported Fields

• Input: Thai text for sentiment classification.
• Output: Sentiment classification result (positive, negative, or neutral).
• Confidence score for each sentiment category.

Additional Capabilities

• Easy integration into existing applications through a user-friendly API.
• Designed for real-time and batch processing.
• Ideal for use cases like social media monitoring, customer feedback analysis, and content sentiment evaluation.

API Reference

Endpoint

GET https://api.iapp.co.th/sentimental-analysis/predict

Query Parameters

Name	Type	Description
text	String	Input Text in Thai language

Headers

Name	Type	Description
apikey	String	API Key

Code Examples

Python

import requests

url = "https://api.iapp.co.th/sentimental-analysis/predict?text={YOUR TEXT}"

payload = {}
headers = {
  'apikey': '{YOUR API KEY}'
}

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

print(response.text)

JavaScript

const axios = require('axios');

let config = {
  method: 'post',
  maxBodyLength: Infinity,
  url: 'https://api.iapp.co.th/sentimental-analysis/predict?text={YOUR TEXT}',
  headers: {
    'apikey': '{YOUR API KEY}'
  }
};

axios.request(config)
.then((response) => {
  console.log(JSON.stringify(response.data));
})
.catch((error) => {
  console.log(error);
});

PHP

<?php

$curl = curl_init();

curl_setopt_array($curl, array(
  CURLOPT_URL => 'https://api.iapp.co.th/sentimental-analysis/predict?text={YOUR%20TEXT}',
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => '',
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 0,
  CURLOPT_FOLLOWLOCATION => true,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => 'POST',
  CURLOPT_HTTPHEADER => array(
    'apikey: {YOUR API KEY}'
  ),
));

$response = curl_exec($curl);

curl_close($curl);
echo $response;

Swift

var request = URLRequest(url: URL(string: "https://api.iapp.co.th/sentimental-analysis/predict?text={YOUR%20TEXT}")!,timeoutInterval: Double.infinity)
request.addValue("{YOUR API KEY}", forHTTPHeaderField: "apikey")

request.httpMethod = "POST"

let task = URLSession.shared.dataTask(with: request) { data, response, error in
  guard let data = data else {
    print(String(describing: error))
    return
  }
  print(String(data: data, encoding: .utf8)!)
}

task.resume()

Kotlin

val mediaType = "text/plain".toMediaType()
val body = "".toRequestBody(mediaType)
val request = Request.Builder()
  .url("https://api.iapp.co.th/sentimental-analysis/predict?text={YOUR TEXT}")
  .post(body)
  .addHeader("apikey", "{YOUR API KEY}")
  .build()
val response = client.newCall(request).execute()

Java

OkHttpClient client = new OkHttpClient().newBuilder()
  .build();
MediaType mediaType = MediaType.parse("text/plain");
RequestBody body = RequestBody.create(mediaType, "");
Request request = new Request.Builder()
  .url("https://api.iapp.co.th/sentimental-analysis/predict?text={YOUR TEXT}")
  .method("POST", body)
  .addHeader("apikey", "{YOUR API KEY}")
  .build();
Response response = client.newCall(request).execute();

Dart

var headers = {
  'apikey': '{YOUR API KEY}'
};
var request = http.Request('POST', Uri.parse('https://api.iapp.co.th/sentimental-analysis/predict?text={YOUR TEXT}'));

request.headers.addAll(headers);

http.StreamedResponse response = await request.send();

if (response.statusCode == 200) {
  print(await response.stream.bytesToString());
}
else {
  print(response.reasonPhrase);
}

Pricing

AI API Service Name	Endpoint	IC Per Characters	On-Premise
Thai Sentimental Analysis [v1.0]	sentimental-analysis	0.1 IC/400 Characters	Contact