Amazon Comprehend
Developer Guide

Detecting Sentiment

To determine the overall emotional tone of text, use the DetectSentiment operation. To detect the sentiment in up to 25 documents in a batch, use the BatchDetectSentiment operation. For more information, see Using the Batch APIs.

Detecting Sentiment Using the AWS Command Line Interface

The following example demonstrates using the DetectSentiment operation with the AWS CLI. This example specifies the language of the input text.

The example is formatted for Unix, Linux, and macOS. For Windows, replace the backslash (\) Unix continuation character at the end of each line with a caret (^).

aws comprehend detect-sentiment \ --region region \ --language-code "en" \ --text "It is raining today in Seattle."

Amazon Comprehend responds with the following:

{ "SentimentScore": { "Mixed": 0.014585512690246105, "Positive": 0.31592071056365967, "Neutral": 0.5985543131828308, "Negative": 0.07093945890665054 }, "Sentiment": "NEUTRAL", "LanguageCode": "en" }

Detecting Sentiment Using the AWS SDK for Java

The following example Java program detects the sentiment of input text. You must specify the language of the input text.

import com.amazonaws.auth.AWSCredentialsProvider; import com.amazonaws.auth.DefaultAWSCredentialsProviderChain; import; import; import; import; public class App { public static void main( String[] args ) { String text = "It is raining today in Seattle"; // Create credentials using a provider chain. For more information, see // AWSCredentialsProvider awsCreds = DefaultAWSCredentialsProviderChain.getInstance(); AmazonComprehend comprehendClient = AmazonComprehendClientBuilder.standard() .withCredentials(awsCreds) .withRegion("region") .build(); // Call detectSentiment API System.out.println("Calling DetectSentiment"); DetectSentimentRequest detectSentimentRequest = new DetectSentimentRequest().withText(text) .withLanguageCode("en"); DetectSentimentResult detectSentimentResult = comprehendClient.detectSentiment(detectSentimentRequest); System.out.println(detectSentimentResult); System.out.println("End of DetectSentiment\n"); System.out.println( "Done" ); } }

Detecting Sentiment Using the AWS SDK for Python (Boto)

The following Python program detects the sentiment of input text. You must specify the language of the input text.

import boto3 import json comprehend = boto3.client(service_name='comprehend', region_name='region') text = "It is raining today in Seattle" print('Calling DetectSentiment') print(json.dumps(comprehend.detect_sentiment(Text=text, LanguageCode='en'), sort_keys=True, indent=4)) print('End of DetectSentiment\n')

Detecting Sentiment Using the AWS SDK for .NET

The .NET example in this section uses the AWS SDK for .NET. You can use the AWS Toolkit for Visual Studio to develop AWS applications using .NET. It includes helpful templates and the AWS Explorer for deploying applications and managing services. For a .NET developer perspective of AWS, see the AWS Guide for .NET Developers.

using System; using Amazon.Comprehend; using Amazon.Comprehend.Model; namespace Comprehend { class Program { static void Main(string[] args) { String text = "It is raining today in Seattle"; AmazonComprehendClient comprehendClient = new AmazonComprehendClient(Amazon.RegionEndpoint.USWest2); // Call DetectKeyPhrases API Console.WriteLine("Calling DetectSentiment"); DetectSentimentRequest detectSentimentRequest = new DetectSentimentRequest() { Text = text, LanguageCode = "en" }; DetectSentimentResponse detectSentimentResponse = comprehendClient.DetectSentiment(detectSentimentRequest); Console.WriteLine(detectSentimentResponse.Sentiment); Console.WriteLine("Done"); } } }