Inspectez le texte donné et identifiez l'opinion émotionnelle dominante.
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Exemple de code
Go
func analyzeSentiment(ctx context.Context, client *language.Client, text string) (*languagepb.AnalyzeSentimentResponse, error) {
return client.AnalyzeSentiment(ctx, &languagepb.AnalyzeSentimentRequest{
Document: &languagepb.Document{
Source: &languagepb.Document_Content{
Content: text,
},
Type: languagepb.Document_PLAIN_TEXT,
},
})
}
Java
// Instantiate the Language client com.google.cloud.language.v1.LanguageServiceClient
try (LanguageServiceClient language = LanguageServiceClient.create()) {
Document doc = Document.newBuilder().setContent(text).setType(Type.PLAIN_TEXT).build();
AnalyzeSentimentResponse response = language.analyzeSentiment(doc);
Sentiment sentiment = response.getDocumentSentiment();
if (sentiment == null) {
System.out.println("No sentiment found");
} else {
System.out.printf("Sentiment magnitude: %.3f\n", sentiment.getMagnitude());
System.out.printf("Sentiment score: %.3f\n", sentiment.getScore());
}
return sentiment;
}Node.js
// Imports the Google Cloud client library
const language = require('@google-cloud/language');
// Creates a client
const client = new language.LanguageServiceClient();
/**
* TODO(developer): Uncomment the following line to run this code.
*/
// const text = 'Your text to analyze, e.g. Hello, world!';
// Prepares a document, representing the provided text
const document = {
content: text,
type: 'PLAIN_TEXT',
};
// Detects the sentiment of the document
const [result] = await client.analyzeSentiment({document});
const sentiment = result.documentSentiment;
console.log('Document sentiment:');
console.log(` Score: ${sentiment.score}`);
console.log(` Magnitude: ${sentiment.magnitude}`);
const sentences = result.sentences;
sentences.forEach(sentence => {
console.log(`Sentence: ${sentence.text.content}`);
console.log(` Score: ${sentence.sentiment.score}`);
console.log(` Magnitude: ${sentence.sentiment.magnitude}`);
});
PHP
use Google\Cloud\Language\V1\Document;
use Google\Cloud\Language\V1\Document\Type;
use Google\Cloud\Language\V1\LanguageServiceClient;
/**
* @param string $text The text to analyze
*/
function analyze_sentiment(string $text): void
{
$languageServiceClient = new LanguageServiceClient();
// Create a new Document, add text as content and set type to PLAIN_TEXT
$document = (new Document())
->setContent($text)
->setType(Type::PLAIN_TEXT);
// Call the analyzeSentiment function
$response = $languageServiceClient->analyzeSentiment($document);
$document_sentiment = $response->getDocumentSentiment();
// Print document information
printf('Document Sentiment:' . PHP_EOL);
printf(' Magnitude: %s' . PHP_EOL, $document_sentiment->getMagnitude());
printf(' Score: %s' . PHP_EOL, $document_sentiment->getScore());
printf(PHP_EOL);
$sentences = $response->getSentences();
foreach ($sentences as $sentence) {
printf('Sentence: %s' . PHP_EOL, $sentence->getText()->getContent());
printf('Sentence Sentiment:' . PHP_EOL);
$sentiment = $sentence->getSentiment();
if ($sentiment) {
printf('Entity Magnitude: %s' . PHP_EOL, $sentiment->getMagnitude());
printf('Entity Score: %s' . PHP_EOL, $sentiment->getScore());
}
print(PHP_EOL);
}
}Python
from google.cloud import language_v1
import six
def sample_analyze_sentiment(content):
client = language_v1.LanguageServiceClient()
# content = 'Your text to analyze, e.g. Hello, world!'
if isinstance(content, six.binary_type):
content = content.decode("utf-8")
type_ = language_v1.Document.Type.PLAIN_TEXT
document = {"type_": type_, "content": content}
response = client.analyze_sentiment(request={"document": document})
sentiment = response.document_sentiment
print("Score: {}".format(sentiment.score))
print("Magnitude: {}".format(sentiment.magnitude))
Étapes suivantes
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