偵測情緒

偵測一些範例文字的情緒。

深入探索

如需包含這個程式碼範例的詳細說明文件，請參閱下列內容：

程式碼範例

Go

如要瞭解如何安裝及使用 Natural Language 的用戶端程式庫，請參閱Natural Language 用戶端程式庫。 詳情請參閱 Natural Language Go API 參考說明文件。

如要向 Natural Language 進行驗證，請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。


// Sample language-quickstart uses the Google Cloud Natural API to analyze the
// sentiment of "Hello, world!".
package main

import (
	"context"
	"fmt"
	"log"

	language "cloud.google.com/go/language/apiv1"
	"cloud.google.com/go/language/apiv1/languagepb"
)

func main() {
	ctx := context.Background()

	// Creates a client.
	client, err := language.NewClient(ctx)
	if err != nil {
		log.Fatalf("Failed to create client: %v", err)
	}
	defer client.Close()

	// Sets the text to analyze.
	text := "Hello, world!"

	// Detects the sentiment of the text.
	sentiment, err := client.AnalyzeSentiment(ctx, &languagepb.AnalyzeSentimentRequest{
		Document: &languagepb.Document{
			Source: &languagepb.Document_Content{
				Content: text,
			},
			Type: languagepb.Document_PLAIN_TEXT,
		},
		EncodingType: languagepb.EncodingType_UTF8,
	})
	if err != nil {
		log.Fatalf("Failed to analyze text: %v", err)
	}

	fmt.Printf("Text: %v\n", text)
	if sentiment.DocumentSentiment.Score >= 0 {
		fmt.Println("Sentiment: positive")
	} else {
		fmt.Println("Sentiment: negative")
	}
}

Java

如要瞭解如何安裝及使用 Natural Language 的用戶端程式庫，請參閱Natural Language 用戶端程式庫。 詳情請參閱 Natural Language Java API 參考說明文件。

如要向 Natural Language 進行驗證，請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

// Imports the Google Cloud client library
import com.google.cloud.language.v1.Document;
import com.google.cloud.language.v1.Document.Type;
import com.google.cloud.language.v1.LanguageServiceClient;
import com.google.cloud.language.v1.Sentiment;

public class QuickstartSample {
  public static void main(String... args) throws Exception {
    // Instantiates a client
    try (LanguageServiceClient language = LanguageServiceClient.create()) {

      // The text to analyze
      String text = "Hello, world!";
      Document doc = Document.newBuilder().setContent(text).setType(Type.PLAIN_TEXT).build();

      // Detects the sentiment of the text
      Sentiment sentiment = language.analyzeSentiment(doc).getDocumentSentiment();

      System.out.printf("Text: %s%n", text);
      System.out.printf("Sentiment: %s, %s%n", sentiment.getScore(), sentiment.getMagnitude());
    }
  }
}

Node.js

如要瞭解如何安裝及使用 Natural Language 的用戶端程式庫，請參閱Natural Language 用戶端程式庫。 詳情請參閱 Natural Language Node.js API 參考說明文件。

如要向 Natural Language 進行驗證，請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

async function quickstart() {
  // Imports the Google Cloud client library
  const language = require('@google-cloud/language');

  // Instantiates a client
  const client = new language.LanguageServiceClient();

  // The text to analyze
  const text = 'Hello, world!';

  const document = {
    content: text,
    type: 'PLAIN_TEXT',
  };

  // Detects the sentiment of the text
  const [result] = await client.analyzeSentiment({document: document});
  const sentiment = result.documentSentiment;

  console.log(`Text: ${text}`);
  console.log(`Sentiment score: ${sentiment.score}`);
  console.log(`Sentiment magnitude: ${sentiment.magnitude}`);
}

PHP

如要瞭解如何安裝及使用 Natural Language 的用戶端程式庫，請參閱這篇文章。

如要向 Natural Language 進行驗證，請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

# Includes the autoloader for libraries installed with composer
require __DIR__ . '/vendor/autoload.php';

# Imports the Google Cloud client library
use Google\Cloud\Language\V2\AnalyzeSentimentRequest;
use Google\Cloud\Language\V2\Client\LanguageServiceClient;
use Google\Cloud\Language\V2\Document;

# Your Google Cloud Platform project ID
$projectId = 'YOUR_PROJECT_ID';

# Instantiates a client
$language = new LanguageServiceClient([
    'projectId' => $projectId
]);

# The text to analyze
$text = 'Hello, world!';
$document = (new Document())
    ->setContent($text)
    ->setType(Document\Type::PLAIN_TEXT);
$analyzeSentimentRequest = (new AnalyzeSentimentRequest())
    ->setDocument($document);

# Detects the sentiment of the text
$response = $language->analyzeSentiment($analyzeSentimentRequest);
foreach ($response->getSentences() as $sentence) {
    $sentiment = $sentence->getSentiment();
    echo 'Text: ' . $sentence->getText()->getContent() . PHP_EOL;
    printf('Sentiment: %s, %s' . PHP_EOL, $sentiment->getScore(), $sentiment->getMagnitude());
}

Python

如要瞭解如何安裝及使用 Natural Language 的用戶端程式庫，請參閱Natural Language 用戶端程式庫。 詳情請參閱 Natural Language Python API 參考說明文件。

如要向 Natural Language 進行驗證，請設定應用程式預設憑證。 詳情請參閱「為本機開發環境設定驗證」。

# Imports the Google Cloud client library.
from google.cloud import language_v1

# Instantiates a client.
client = language_v1.LanguageServiceClient()

# The text to analyze.
text = "Hello, world!"
document = language_v1.types.Document(
    content=text, type_=language_v1.types.Document.Type.PLAIN_TEXT
)

# Detects the sentiment of the text.
sentiment = client.analyze_sentiment(
    request={"document": document}
).document_sentiment

print(f"Text: {text}")
print(f"Sentiment: {sentiment.score}, {sentiment.magnitude}")

後續步驟

如要搜尋及篩選其他 Google Cloud 產品的程式碼範例，請參閱Google Cloud 範例瀏覽器。