Melakukan analisis sentimen menggunakan library klien

Halaman ini menunjukkan cara memulai Cloud Natural Language API dalam bahasa pemrograman favorit Anda menggunakan Library Klien Google Cloud.

Sebelum memulai

  1. Sign in to your Google Account.

    If you don't already have one, sign up for a new account.

  2. Install the Google Cloud CLI.

  3. To initialize the gcloud CLI, run the following command: 

    gcloud init

  4. Buat atau pilih project Google Cloud.

    • Membuat project Google Cloud:

      gcloud projects create PROJECT_ID

      Ganti PROJECT_ID dengan nama untuk project Google Cloud yang Anda buat.

    • Pilih project Google Cloud yang Anda buat:

      gcloud config set project PROJECT_ID

      Ganti PROJECT_ID dengan nama project Google Cloud Anda.

  5. Make sure that billing is enabled for your Google Cloud project.

  6. Aktifkan API Cloud Natural Language: 

    gcloud services enable language.googleapis.com

  7. Buat kredensial autentikasi lokal untuk Akun Google Anda: 

    gcloud auth application-default login
  8. Install the Google Cloud CLI.

  9. To initialize the gcloud CLI, run the following command: 

    gcloud init

  10. Buat atau pilih project Google Cloud.

    • Membuat project Google Cloud:

      gcloud projects create PROJECT_ID

      Ganti PROJECT_ID dengan nama untuk project Google Cloud yang Anda buat.

    • Pilih project Google Cloud yang Anda buat:

      gcloud config set project PROJECT_ID

      Ganti PROJECT_ID dengan nama project Google Cloud Anda.

  11. Make sure that billing is enabled for your Google Cloud project.

  12. Aktifkan API Cloud Natural Language: 

    gcloud services enable language.googleapis.com

  13. Buat kredensial autentikasi lokal untuk Akun Google Anda: 

    gcloud auth application-default login

Menginstal library klien

Go

go get cloud.google.com/go/language/apiv1

Java

If you are using Maven, add the following to your pom.xml file. For more information about BOMs, see The Google Cloud Platform Libraries BOM.

<dependencyManagement>
  <dependencies>
    <dependency>
      <groupId>com.google.cloud</groupId>
      <artifactId>libraries-bom</artifactId>
      <version>26.50.0</version>
      <type>pom</type>
      <scope>import</scope>
    </dependency>
  </dependencies>
</dependencyManagement>

<dependencies>
  <dependency>
    <groupId>com.google.cloud</groupId>
    <artifactId>google-cloud-language</artifactId>
  </dependency>
</dependencies>

If you are using Gradle, add the following to your dependencies:

implementation 'com.google.cloud:google-cloud-language:2.54.0'

If you are using sbt, add the following to your dependencies:

libraryDependencies += "com.google.cloud" % "google-cloud-language" % "2.54.0"

If you're using Visual Studio Code, IntelliJ, or Eclipse, you can add client libraries to your project using the following IDE plugins:

The plugins provide additional functionality, such as key management for service accounts. Refer to each plugin's documentation for details.

Node.js

Sebelum menginstal library, pastikan Anda telah menyiapkan lingkungan untuk pengembangan Node.js.

npm install --save @google-cloud/language

Python

Sebelum menginstal library, pastikan Anda telah menyiapkan lingkungan untuk pengembangan Python.

pip install --upgrade google-cloud-language

Menganalisis beberapa teks

Sekarang Anda dapat menggunakan Natural Language API untuk menganalisis beberapa teks. Jalankan kode berikut untuk melakukan analisis sentimen teks pertama Anda:

Go


// 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

// 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

Sebelum menjalankan contoh, pastikan Anda telah menyiapkan lingkungan untuk pengembangan Node.js.

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}`);
}

Python

Sebelum menjalankan contoh, pastikan Anda telah menyiapkan lingkungan untuk pengembangan Python.

# 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}")

Selamat! Anda telah mengirimkan permintaan pertama ke Natural Language API.

Bagaimana hasilnya?

Pembersihan

Agar tidak menimbulkan biaya pada akun Google Cloud Anda untuk resource yang digunakan pada halaman ini, hapus project Google Cloud yang berisi resource tersebut.

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