multilingual sentiment analysis

Understand the underlying tone of the message for sentences in Spanish, Portuguese and Chinese. We will add more languages over time, watch this space for sentiment analysis in your preferred language.

Select a Language

Positive

Neutral

Negative

Ready to Integrate? Check out the API wrappers below

For setup and installation instruction, please visit our Github Page
import paralleldots.ParallelDots;
// Get your API key here
ParallelDots pd = new ParallelDots("<YOUR_API_KEY>");
//Examples | Available languages : Spanish (es), Portugues (pt), Chinese (cn)
import paralleldots.ParallelDots;
ParallelDots pd = new ParallelDots();
String multilang = pd.multilang('Me siento muy enfermo hoy', 'es');
System.out.println(multilang);
//Response
{
	"sentiment": "positive", 
	"confidence_score": 0.845703
}
For setup and installation instruction, please visit our Github Page
from paralleldots import set_api_key, get_api_key
# Get your API key here
set_api_key(<YOUR_API_KEY>)
//Examples | Available languages : Spanish (es), Portugues (pt), Chinese (cn)
get_api_key()
from paralleldots import similarity, ner, taxonomy, sentiment, keywords, intent, emotion, multilang, abuse
multilang('Me siento muy enfermo hoy', 'es')
#Response
{
	"sentiment": "positive", 
	"confidence_score": 0.845703
}
For setup and installation instruction, please visit our Github Page
require 'paralleldots'
# Get your API key here
set_api_key(<YOUR_API_KEY>)
//Examples | Available languages : Spanish (es), Portugues (pt), Chinese (cn)
get_api_key()
require 'paralleldots'
multilang('Me siento muy enfermo hoy', 'es')
#Response
{
	"sentiment": "positive", 
	"confidence_score": 0.845703
}
For setup and installation instruction, please visit our Github Page
using ParallelDots
# Get your API key here
ParallelDots.api pd = new ParallelDots.api("<YOUR_API_KEY>");
//Examples | Available languages : Spanish (es), Portugues (pt), Chinese (cn)
var multilang = pd.multilang('Me siento muy enfermo hoy', 'es');
Console.WriteLine(multilang);
#Response
{
	"sentiment": "positive", 
	"confidence_score": 0.845703
}
For setup and installation instruction, please visit our Github Page
require(__DIR__ . '/vendor/paralleldots/apis/autoload.php');
# Get your API key here
set_api_key("<YOUR_API_KEY>");
get_api_key();
//Examples | Available languages : Spanish (es), Portugues (pt), Chinese (cn)
require(__DIR__ . '/vendor/paralleldots/apis/autoload.php');
multilang('Me siento muy enfermo hoy', 'es');
#Response
{
	"sentiment": "positive", 
	"confidence_score": 0.845703
}
how our multilingual sentiment analysis api works?

It uses Long Short Term Memory (LSTM) algorithms to classify a text into different. LSTMs model sentences as chain of forget-remember decisions based on context. It is trained on social media data and news data differently for handling casual and formal language. We also have trained this algorithm for various custom datasets for different clients.

multilingual sentiment analysis use cases

Sentiment Analysis can come out as the ultimate tool for marketing. You can leverage the power of sentiment analysis to read and analyze the sentiments of online conversation about your brand. It can also provide a fast solution to categorize your product reviews. You can identify influencers and categorize them as advocates or detractors of your brand. Additionally, Sentiment Analysis can aid you in market and competitive research. Read more about the application and use cases of sentiment analysis here.With our Multilingual Sentiment Analysis API, you are not restricted by language barrier as it can be done in your preferred language.

why our multilingual sentiment analysis api ?
Accurate

Highly accurate classification of unstructured textual data.

Real Time

State of the art technology to provide accurate results real-time.

Customizable

Can be trained on custom dataset to obtain similar accuracy and performance.