public async Task AnalyzeSentimentBatchConvenienceWithLanguageAndStatisticsTest()
{
TextAnalyticsClient client = GetClient();
var documents = batchConvenienceDocuments;
AnalyzeSentimentResultCollection results = await client.AnalyzeSentimentBatchAsync(documents, "en", new TextAnalyticsRequestOptions { IncludeStatistics = true });
foreach (AnalyzeSentimentResult docs in results)
{
CheckAnalyzeSentimentProperties(docs.DocumentSentiment);
}
Assert.AreEqual("Positive", results[0].DocumentSentiment.Sentiment.ToString());
Assert.AreEqual("Negative", results[1].DocumentSentiment.Sentiment.ToString());
Assert.IsNotNull(results.Statistics.ValidDocumentCount);
Assert.IsNotNull(results.Statistics.DocumentCount);
Assert.IsNotNull(results.Statistics.TransactionCount);
Assert.IsNotNull(results.Statistics.InvalidDocumentCount);
}
public async Task AnalyzeSentimentBatchWithErrorTest()
{
TextAnalyticsClient client = GetClient();
var inputs = new List <string>
{
"That was the best day of my life!",
"",
"I'm not sure how I feel about this product."
};
AnalyzeSentimentResultCollection results = await client.AnalyzeSentimentBatchAsync(inputs);
Assert.IsTrue(!results[0].HasError);
Assert.IsTrue(!results[2].HasError);
var exceptionMessage = "Cannot access result for document 1, due to error InvalidDocument: Document text is empty.";
Assert.IsTrue(results[1].HasError);
InvalidOperationException ex = Assert.Throws <InvalidOperationException>(() => results[1].DocumentSentiment.GetType());
Assert.AreEqual(exceptionMessage, ex.Message);
}
public async Task AnalyzeSentimentBatchConvenienceWithOpinionMiningTest()
{
TextAnalyticsClient client = GetClient();
var documents = new List <string>
{
"The park was clean and pretty. The bathrooms and restaurant were not clean.",
"The food and service is not good."
};
AnalyzeSentimentResultCollection results = await client.AnalyzeSentimentBatchAsync(documents, options : new AnalyzeSentimentOptions()
{
IncludeOpinionMining = true
});
foreach (AnalyzeSentimentResult docs in results)
{
CheckAnalyzeSentimentProperties(docs.DocumentSentiment, opinionMining: true);
}
Assert.AreEqual("Mixed", results[0].DocumentSentiment.Sentiment.ToString());
Assert.AreEqual("Negative", results[1].DocumentSentiment.Sentiment.ToString());
}
public async Task AnalyzeSentimentBatchConvenienceWithStatisticsAndCancellationTest()
{
TextAnalyticsClient client = GetClient();
var documents = batchConvenienceDocuments;
AnalyzeSentimentResultCollection results = await client.AnalyzeSentimentBatchAsync(documents, options : new AnalyzeSentimentOptions()
{
IncludeStatistics = true
}, cancellationToken : default);
foreach (AnalyzeSentimentResult docs in results)
{
CheckAnalyzeSentimentProperties(docs.DocumentSentiment);
}
Assert.AreEqual("Positive", results[0].DocumentSentiment.Sentiment.ToString());
Assert.AreEqual("Negative", results[1].DocumentSentiment.Sentiment.ToString());
Assert.IsNotNull(results.Statistics.ValidDocumentCount);
Assert.IsNotNull(results.Statistics.DocumentCount);
Assert.IsNotNull(results.Statistics.TransactionCount);
Assert.IsNotNull(results.Statistics.InvalidDocumentCount);
}
public async Task AnalyzeSentimentBatchTest()
{
TextAnalyticsClient client = GetClient();
var inputs = new List <TextDocumentInput>
{
new TextDocumentInput("1", "Pike Place Market is my favorite Seattle attraction. We had so much fun there.")
{
Language = "en",
},
new TextDocumentInput("2", "Esta comida no me gusta. Siempre que la como me enfermo.")
{
Language = "es",
}
};
AnalyzeSentimentResultCollection results = await client.AnalyzeSentimentBatchAsync(inputs);
Assert.AreEqual("Positive", results[0].DocumentSentiment.Sentiment.ToString());
Assert.AreEqual("Negative", results[1].DocumentSentiment.Sentiment.ToString());
foreach (AnalyzeSentimentResult docs in results)
{
DocumentSentiment docSentiment = docs.DocumentSentiment;
Assert.IsNotNull(docSentiment.ConfidenceScores.Positive);
Assert.IsNotNull(docSentiment.ConfidenceScores.Neutral);
Assert.IsNotNull(docSentiment.ConfidenceScores.Negative);
foreach (var sentence in docSentiment.Sentences)
{
Assert.IsNotNull(sentence.ConfidenceScores.Positive);
Assert.IsNotNull(sentence.ConfidenceScores.Neutral);
Assert.IsNotNull(sentence.ConfidenceScores.Negative);
Assert.IsNotNull(sentence.Offset);
Assert.IsNotNull(sentence.Length);
}
}
}
public async Task AnalyzeSentimentBatchConvenienceWithStatisticsTest()
{
TextAnalyticsClient client = GetClient();
var documents = new List <string>
{
"That was the best day of my life!. I had a lot of fun at the park.",
"I'm not sure how I feel about this product. It is complicated."
};
AnalyzeSentimentResultCollection results = await client.AnalyzeSentimentBatchAsync(documents, "en", new TextAnalyticsRequestOptions { IncludeStatistics = true });
foreach (AnalyzeSentimentResult docs in results)
{
CheckAnalyzeSentimentProperties(docs.DocumentSentiment);
}
Assert.AreEqual("Positive", results[0].DocumentSentiment.Sentiment.ToString());
Assert.AreEqual("Negative", results[1].DocumentSentiment.Sentiment.ToString());
Assert.IsNotNull(results.Statistics.ValidDocumentCount);
Assert.IsNotNull(results.Statistics.DocumentCount);
Assert.IsNotNull(results.Statistics.TransactionCount);
Assert.IsNotNull(results.Statistics.InvalidDocumentCount);
}
public async Task AnalyzeSentimentWithOpinionMiningAsync()
{
string endpoint = TestEnvironment.Endpoint;
string apiKey = TestEnvironment.ApiKey;
// Instantiate a client that will be used to call the service.
var client = new TextAnalyticsClient(new Uri(endpoint), new AzureKeyCredential(apiKey));
var documents = new List <string>
{
"The food and service were unacceptable, but the concierge were nice.",
"The rooms were beautiful. The AC was good and quiet.",
"The breakfast was good, but the toilet was smelly.",
"Loved this hotel - good breakfast - nice shuttle service - clean rooms.",
"I had a great unobstructed view of the Microsoft campus.",
"Nice rooms but bathrooms were old and the toilet was dirty when we arrived.",
"We changed rooms as the toilet smelled."
};
AnalyzeSentimentResultCollection reviews = await client.AnalyzeSentimentBatchAsync(documents, options : new AnalyzeSentimentOptions()
{
AdditionalSentimentAnalyses = AdditionalSentimentAnalyses.OpinionMining
});
Dictionary <string, int> complaints = GetComplaint(reviews);
var negativeAspect = complaints.Aggregate((l, r) => l.Value > r.Value ? l : r).Key;
Console.WriteLine($"Alert! major complaint is *{negativeAspect}*");
Console.WriteLine();
Console.WriteLine("---All complaints:");
foreach (KeyValuePair <string, int> complaint in complaints)
{
Console.WriteLine($" {complaint.Key}, {complaint.Value}");
}
}
public static async Task <IActionResult> AnalyzeThread(
[HttpTrigger(AuthorizationLevel.Function, "get", "post", Route = null)] HttpRequest req,
ILogger log)
{
var client = HttpClientFactory.Create();
var url = new Uri(req.Query["url"].FirstOrDefault());
var postJson = await client.GetStringAsync(url.AbsoluteUri + ".json");
var listings = JsonConvert.DeserializeObject <List <Listing> >(postJson);
var comments = new List <(string id, string comment)>();
foreach (var child in from listing in listings
from child in listing.data.children
where child.IsComment
select child)
{
await AddCommentToList(comments, child.data);
}
log.LogInformation($"Found a total of '{comments.Count}' comments.");
var commentsToAnalyze = comments.Select(c => new TextDocumentInput(c.id, c.comment)).ToList();
TextAnalyticsClient textAnalyticClient = new TextAnalyticsClient(endpoint, credentials);
IEnumerable <string> sentimentResult = (await textAnalyticClient.AnalyzeSentimentBatchAsync(commentsToAnalyze)).Value.Select(x => x.DocumentSentiment.Sentiment.ToString());
Func <string, decimal> percentage = (sentiment) => sentimentResult.Where(x => x == sentiment).Count() / (decimal)commentsToAnalyze.Count * 100;
var positiveString = $"{Math.Round(percentage("Positive"), 1)}% positive";
var negativeString = $"{Math.Round(percentage("Negative"), 1)}% negative";
var neutralString = $"{Math.Round(percentage("Neutral"), 1)}% neutral";
var mixedString = $"{Math.Round(percentage("Mixed"), 1)}% mixed";
return(new OkObjectResult($"For URL {url}\r\n{comments.Count} comments analyzed with {positiveString}, {negativeString}, {neutralString}, and {mixedString}."));
}
public async Task AnalyzeSentimentBatchConvenienceAsync()
{
string endpoint = TestEnvironment.Endpoint;
string apiKey = TestEnvironment.ApiKey;
// Instantiate a client that will be used to call the service.
var client = new TextAnalyticsClient(new Uri(endpoint), new AzureKeyCredential(apiKey), CreateSampleOptions());
string documentA = @"The food and service were unacceptable, but the concierge were nice.
After talking to them about the quality of the food and the process
to get room service they refunded the money we spent at the restaurant and
gave us a voucher for nearby restaurants.";
string documentB = @"Nice rooms! I had a great unobstructed view of the Microsoft campus but bathrooms
were old and the toilet was dirty when we arrived. It was close to bus stops and
groceries stores.
If you want to be close to campus I will recommend it, otherwise, might be
better to stay in a cleaner one";
string documentC = @"The rooms were beautiful. The AC was good and quiet, which was key for us as outside
it was 100F and our baby was getting uncomfortable because of the heat. The breakfast
was good too with good options and good servicing times.
The thing we didn't like was that the toilet in our bathroom was smelly.
It could have been that the toilet was not cleaned before we arrived.";
string documentD = string.Empty;
var documents = new List <string>
{
documentA,
documentB,
documentC,
documentD
};
Response <AnalyzeSentimentResultCollection> response = await client.AnalyzeSentimentBatchAsync(documents);
AnalyzeSentimentResultCollection sentimentPerDocuments = response.Value;
int i = 0;
Console.WriteLine($"Results of \"Sentiment Analysis\" Model, version: \"{sentimentPerDocuments.ModelVersion}\"");
Console.WriteLine("");
foreach (AnalyzeSentimentResult sentimentInDocument in sentimentPerDocuments)
{
Console.WriteLine($"On document with Text: \"{documents[i++]}\"");
Console.WriteLine("");
if (sentimentInDocument.HasError)
{
Console.WriteLine(" Error!");
Console.WriteLine($" Document error: {sentimentInDocument.Error.ErrorCode}.");
Console.WriteLine($" Message: {sentimentInDocument.Error.Message}");
}
else
{
Console.WriteLine($"Document sentiment is {sentimentInDocument.DocumentSentiment.Sentiment}, with confidence scores: ");
Console.WriteLine($" Positive confidence score: {sentimentInDocument.DocumentSentiment.ConfidenceScores.Positive}.");
Console.WriteLine($" Neutral confidence score: {sentimentInDocument.DocumentSentiment.ConfidenceScores.Neutral}.");
Console.WriteLine($" Negative confidence score: {sentimentInDocument.DocumentSentiment.ConfidenceScores.Negative}.");
Console.WriteLine("");
Console.WriteLine($" Sentence sentiment results:");
foreach (SentenceSentiment sentimentInSentence in sentimentInDocument.DocumentSentiment.Sentences)
{
Console.WriteLine($" For sentence: \"{sentimentInSentence.Text}\"");
Console.WriteLine($" Sentiment is {sentimentInSentence.Sentiment}, with confidence scores: ");
Console.WriteLine($" Positive confidence score: {sentimentInSentence.ConfidenceScores.Positive}.");
Console.WriteLine($" Neutral confidence score: {sentimentInSentence.ConfidenceScores.Neutral}.");
Console.WriteLine($" Negative confidence score: {sentimentInSentence.ConfidenceScores.Negative}.");
Console.WriteLine("");
}
}
Console.WriteLine("");
}
}
public void AnalyzeSentimentBatchWithNullIdTest()
{
TextAnalyticsClient client = GetClient();
var documents = new List <TextDocumentInput> {
new TextDocumentInput(null, "Hello world")
};
RequestFailedException ex = Assert.ThrowsAsync <RequestFailedException>(async() => await client.AnalyzeSentimentBatchAsync(documents));
Assert.AreEqual(TextAnalyticsErrorCode.InvalidDocument, ex.ErrorCode);
}
public async Task AnalyzeSentimentBatchAsync()
{
string endpoint = TestEnvironment.Endpoint;
string apiKey = TestEnvironment.ApiKey;
// Instantiate a client that will be used to call the service.
var client = new TextAnalyticsClient(new Uri(endpoint), new AzureKeyCredential(apiKey));
var documents = new List <TextDocumentInput>
{
new TextDocumentInput("1", "That was the best day of my life!")
{
Language = "en",
},
new TextDocumentInput("2", "This food is very bad. Everyone who ate with us got sick.")
{
Language = "en",
},
new TextDocumentInput("3", "I'm not sure how I feel about this product.")
{
Language = "en",
},
new TextDocumentInput("4", "Pike Place Market is my favorite Seattle attraction. We had so much fun there.")
{
Language = "en",
}
};
AnalyzeSentimentResultCollection results = await client.AnalyzeSentimentBatchAsync(documents, new TextAnalyticsRequestOptions { IncludeStatistics = true });
int i = 0;
Console.WriteLine($"Results of Azure Text Analytics \"Sentiment Analysis\" Model, version: \"{results.ModelVersion}\"");
Console.WriteLine("");
foreach (AnalyzeSentimentResult result in results)
{
TextDocumentInput document = documents[i++];
Console.WriteLine($"On document (Id={document.Id}, Language=\"{document.Language}\", Text=\"{document.Text}\"):");
if (result.HasError)
{
Console.WriteLine($" Document error: {result.Error.ErrorCode}.");
Console.WriteLine($" Message: {result.Error.Message}.");
}
else
{
Console.WriteLine($"Document sentiment is {result.DocumentSentiment.Sentiment}, with confidence scores: ");
Console.WriteLine($" Positive confidence score: {result.DocumentSentiment.ConfidenceScores.Positive}.");
Console.WriteLine($" Neutral confidence score: {result.DocumentSentiment.ConfidenceScores.Neutral}.");
Console.WriteLine($" Negative confidence score: {result.DocumentSentiment.ConfidenceScores.Negative}.");
Console.WriteLine($" Sentence sentiment results:");
foreach (SentenceSentiment sentenceSentiment in result.DocumentSentiment.Sentences)
{
Console.WriteLine($" For sentence: \"{sentenceSentiment.Text}\"");
Console.WriteLine($" Sentiment is {sentenceSentiment.Sentiment}, with confidence scores: ");
Console.WriteLine($" Positive confidence score: {sentenceSentiment.ConfidenceScores.Positive}.");
Console.WriteLine($" Neutral confidence score: {sentenceSentiment.ConfidenceScores.Neutral}.");
Console.WriteLine($" Negative confidence score: {sentenceSentiment.ConfidenceScores.Negative}.");
}
Console.WriteLine($" Document statistics:");
Console.WriteLine($" Character count (in Unicode graphemes): {result.Statistics.CharacterCount}");
Console.WriteLine($" Transaction count: {result.Statistics.TransactionCount}");
Console.WriteLine("");
}
}
Console.WriteLine($"Batch operation statistics:");
Console.WriteLine($" Document count: {results.Statistics.DocumentCount}");
Console.WriteLine($" Valid document count: {results.Statistics.ValidDocumentCount}");
Console.WriteLine($" Invalid document count: {results.Statistics.InvalidDocumentCount}");
Console.WriteLine($" Transaction count: {results.Statistics.TransactionCount}");
Console.WriteLine("");
}
public async Task AnalyzeSentimentBatchAsync()
{
string endpoint = TestEnvironment.Endpoint;
string apiKey = TestEnvironment.ApiKey;
// Instantiate a client that will be used to call the service.
var client = new TextAnalyticsClient(new Uri(endpoint), new AzureKeyCredential(apiKey), CreateSampleOptions());
string documentA = @"The food and service were unacceptable, but the concierge were nice.
After talking to them about the quality of the food and the process
to get room service they refunded the money we spent at the restaurant and
gave us a voucher for nearby restaurants.";
string documentB = @"Nos hospedamos en el Hotel Foo la semana pasada por nuestro aniversario. La gerencia
sabía de nuestra celebración y me ayudaron a tenerle una sorpresa a mi pareja.
La habitación estaba limpia y decorada como yo había pedido. Una gran experiencia.
El próximo año volveremos.";
string documentC = @"The rooms were beautiful. The AC was good and quiet, which was key for us as outside
it was 100F and our baby was getting uncomfortable because of the heat. The breakfast
was good too with good options and good servicing times.
The thing we didn't like was that the toilet in our bathroom was smelly.
It could have been that the toilet was not cleaned before we arrived.
Either way it was very uncomfortable. Once we notified the staff, they came and cleaned
it and left candles.";
var documents = new List <TextDocumentInput>
{
new TextDocumentInput("1", documentA)
{
Language = "en",
},
new TextDocumentInput("2", documentB)
{
Language = "es",
},
new TextDocumentInput("3", documentC)
{
Language = "en",
},
new TextDocumentInput("4", string.Empty)
};
var options = new AnalyzeSentimentOptions {
IncludeStatistics = true
};
Response <AnalyzeSentimentResultCollection> response = await client.AnalyzeSentimentBatchAsync(documents, options);
AnalyzeSentimentResultCollection sentimentPerDocuments = response.Value;
int i = 0;
Console.WriteLine($"Results of \"Sentiment Analysis\" Model, version: \"{sentimentPerDocuments.ModelVersion}\"");
Console.WriteLine("");
foreach (AnalyzeSentimentResult sentimentInDocument in sentimentPerDocuments)
{
TextDocumentInput document = documents[i++];
Console.WriteLine($"On document (Id={document.Id}, Language=\"{document.Language}\"):");
if (sentimentInDocument.HasError)
{
Console.WriteLine(" Error!");
Console.WriteLine($" Document error: {sentimentInDocument.Error.ErrorCode}.");
Console.WriteLine($" Message: {sentimentInDocument.Error.Message}");
}
else
{
Console.WriteLine($"Document sentiment is {sentimentInDocument.DocumentSentiment.Sentiment}, with confidence scores: ");
Console.WriteLine($" Positive confidence score: {sentimentInDocument.DocumentSentiment.ConfidenceScores.Positive}.");
Console.WriteLine($" Neutral confidence score: {sentimentInDocument.DocumentSentiment.ConfidenceScores.Neutral}.");
Console.WriteLine($" Negative confidence score: {sentimentInDocument.DocumentSentiment.ConfidenceScores.Negative}.");
Console.WriteLine("");
Console.WriteLine($" Sentence sentiment results:");
foreach (SentenceSentiment sentimentInSentence in sentimentInDocument.DocumentSentiment.Sentences)
{
Console.WriteLine($" For sentence: \"{sentimentInSentence.Text}\"");
Console.WriteLine($" Sentiment is {sentimentInSentence.Sentiment}, with confidence scores: ");
Console.WriteLine($" Positive confidence score: {sentimentInSentence.ConfidenceScores.Positive}.");
Console.WriteLine($" Neutral confidence score: {sentimentInSentence.ConfidenceScores.Neutral}.");
Console.WriteLine($" Negative confidence score: {sentimentInSentence.ConfidenceScores.Negative}.");
Console.WriteLine("");
}
Console.WriteLine($" Document statistics:");
Console.WriteLine($" Character count: {sentimentInDocument.Statistics.CharacterCount}");
Console.WriteLine($" Transaction count: {sentimentInDocument.Statistics.TransactionCount}");
}
Console.WriteLine("");
}
Console.WriteLine($"Batch operation statistics:");
Console.WriteLine($" Document count: {sentimentPerDocuments.Statistics.DocumentCount}");
Console.WriteLine($" Valid document count: {sentimentPerDocuments.Statistics.ValidDocumentCount}");
Console.WriteLine($" Invalid document count: {sentimentPerDocuments.Statistics.InvalidDocumentCount}");
Console.WriteLine($" Transaction count: {sentimentPerDocuments.Statistics.TransactionCount}");
}