static string SentimentAnalysisExample(TextAnalyticsClient client, string text)
{
string inputText = text;
string response = "";
DocumentSentiment documentSentiment = client.AnalyzeSentiment(inputText);
Console.WriteLine($"Document sentiment: {documentSentiment.Sentiment}\n");
response = response + $"Document sentiment: {documentSentiment.Sentiment}\n";
var si = new StringInfo(inputText);
foreach (var sentence in documentSentiment.Sentences)
{
Console.WriteLine($" Text: \"{si.SubstringByTextElements(sentence.GraphemeOffset, sentence.GraphemeLength)}\"");
response = response + $" Text: \"{si.SubstringByTextElements(sentence.GraphemeOffset, sentence.GraphemeLength)}\"\n";
Console.WriteLine($" Sentence sentiment: {sentence.Sentiment}");
response = response + $" Sentence sentiment: {sentence.Sentiment}" + "\n";
Console.WriteLine($" Positive score: {sentence.ConfidenceScores.Positive:0.00}");
response = response + $" Positive score: {sentence.ConfidenceScores.Positive:0.00} ";
Console.WriteLine($" Negative score: {sentence.ConfidenceScores.Negative:0.00}");
response = response + $" Negative score: {sentence.ConfidenceScores.Negative:0.00} ";
Console.WriteLine($" Neutral score: {sentence.ConfidenceScores.Neutral:0.00}\n");
response = response + $" Neutral score: {sentence.ConfidenceScores.Neutral:0.00}\n\n";
}
return(response);
}
public void AnalyzeSentimentBatchConvenience()
{
string endpoint = Environment.GetEnvironmentVariable("TEXT_ANALYTICS_ENDPOINT");
string subscriptionKey = Environment.GetEnvironmentVariable("TEXT_ANALYTICS_SUBSCRIPTION_KEY");
var client = new TextAnalyticsClient(new Uri(endpoint), subscriptionKey);
var inputs = new List <string>
{
"That was the best day of my life!",
"This food is very bad.",
"I'm not sure how I feel about this product.",
"Pike place market is my favorite Seattle attraction.",
};
Debug.WriteLine($"Analyzing sentiment for inputs:");
foreach (string input in inputs)
{
Debug.WriteLine($" {input}");
}
#region Snippet:TextAnalyticsSample2AnalyzeSentimentConvenience
AnalyzeSentimentResultCollection results = client.AnalyzeSentiment(inputs);
#endregion
Debug.WriteLine($"Predicted sentiments are:");
foreach (AnalyzeSentimentResult result in results)
{
TextSentiment sentiment = result.DocumentSentiment;
Debug.WriteLine($"Document sentiment is {sentiment.SentimentClass.ToString()}, with scores: ");
Debug.WriteLine($" Positive score: {sentiment.PositiveScore:0.00}.");
Debug.WriteLine($" Neutral score: {sentiment.NeutralScore:0.00}.");
Debug.WriteLine($" Negative score: {sentiment.NegativeScore:0.00}.");
}
}
public static string AnalyzeSentiment(string feedback)
{
var client = new TextAnalyticsClient(endpoint, credentials);
DocumentSentiment documentSentiment = client.AnalyzeSentiment(feedback);
return(documentSentiment.Sentiment.ToString());
}
private static void SentimentAnalysis(string blobName, string recognizedText)
{
TextAnalyticsClient client = new TextAnalyticsClient(_textAnalyticsEndpoint, _textAnalyticsApiKeyCredential);
DocumentSentiment documentSentiment = client.AnalyzeSentiment(recognizedText);
if (documentSentiment != null)
{
_logger.LogInformation($"{blobName}: Text sentiment: {documentSentiment.Sentiment}");
//Extract Key keyPhrases
Response <IReadOnlyCollection <string> > response = client.ExtractKeyPhrases(recognizedText);
IEnumerable <string> keyPhrases = response.Value;
StringBuilder keyPhrasesValues = new StringBuilder();
foreach (string keyPhrase in keyPhrases)
{
keyPhrasesValues.Append(keyPhrase);
}
SaveTrancription(blobName, recognizedText, documentSentiment.Sentiment.ToString(), keyPhrasesValues.ToString());
}
else
{
_logger.LogError($"{blobName}: Unable to process sentiment");
}
}
public string AnalyzeSentiment(string inputMessage)
{
var client = new TextAnalyticsClient(endpoint, credentials);
DocumentSentiment documentSentiment = client.AnalyzeSentiment(inputMessage);
return(documentSentiment.Sentiment.ToString());
}
public void AnalyzeSentiment()
{
string endpoint = TestEnvironment.Endpoint;
string apiKey = TestEnvironment.ApiKey;
var client = new TextAnalyticsClient(new Uri(endpoint), new AzureKeyCredential(apiKey));
#region Snippet:AnalyzeSentiment
string document = @"I had the best day of my life. I decided to go sky-diving and it
made me appreciate my whole life so much more.
I developed a deep-connection with my instructor as well, and I
feel as if I've made a life-long friend in her.";
try
{
Response <DocumentSentiment> response = client.AnalyzeSentiment(document);
DocumentSentiment docSentiment = response.Value;
Console.WriteLine($"Sentiment was {docSentiment.Sentiment}, with confidence scores: ");
Console.WriteLine($" Positive confidence score: {docSentiment.ConfidenceScores.Positive}.");
Console.WriteLine($" Neutral confidence score: {docSentiment.ConfidenceScores.Neutral}.");
Console.WriteLine($" Negative confidence score: {docSentiment.ConfidenceScores.Negative}.");
}
catch (RequestFailedException exception)
{
Console.WriteLine($"Error Code: {exception.ErrorCode}");
Console.WriteLine($"Message: {exception.Message}");
}
#endregion
}
public void AnalyzeSentimentBatch()
{
string endpoint = Environment.GetEnvironmentVariable("TEXT_ANALYTICS_ENDPOINT");
string subscriptionKey = Environment.GetEnvironmentVariable("TEXT_ANALYTICS_SUBSCRIPTION_KEY");
// Instantiate a client that will be used to call the service.
var client = new TextAnalyticsClient(new Uri(endpoint), subscriptionKey);
var inputs = new List <string>
{
"That was the best day of my life!",
"This food is very bad.",
"I'm not sure how I feel about this product.",
"Pike place market is my favorite Seattle attraction."
};
Debug.WriteLine($"Analyzing sentiment for inputs:");
foreach (var input in inputs)
{
Debug.WriteLine($" {input}");
}
var sentiments = client.AnalyzeSentiment(inputs).Value;
Debug.WriteLine($"Predicted sentiments are:");
foreach (var sentiment in sentiments)
{
Debug.WriteLine($"Document sentiment is {sentiment.SentimentClass.ToString()}, with scores: ");
Debug.WriteLine($" Positive score: {sentiment.PositiveScore:0.00}.");
Debug.WriteLine($" Neutral score: {sentiment.NeutralScore:0.00}.");
Debug.WriteLine($" Negative score: {sentiment.NegativeScore:0.00}.");
}
}
public static async Task <IActionResult> Run(
[HttpTrigger(AuthorizationLevel.Anonymous, "get", "post", Route = null)] HttpRequest req,
ILogger log)
{
log.LogInformation("C# HTTP trigger function processed a request.");
AzureKeyCredential credentials = new AzureKeyCredential("<reemplazar-con-tu-text-analytics-key>");
Uri endpoint = new Uri("<reemplazar-con-tu-endpoint-analytics>");
string text = req.Query["body"];
var client = new TextAnalyticsClient(endpoint, credentials);
string requestBody = await new StreamReader(req.Body).ReadToEndAsync();
dynamic data = JsonConvert.DeserializeObject(requestBody);
text = text ?? data?.body;
if (!string.IsNullOrEmpty(text))
{
DocumentSentiment documentSentiment = client.AnalyzeSentiment(text);
return(new OkObjectResult(documentSentiment.Sentiment.ToString()));
}
else
{
return(new OkObjectResult("This HTTP triggered function executed successfully. Pass a text in the query string or in the request body for a personalized response."));
}
}
static double[] SentimentAnalysisPercentages(TextAnalyticsClient client, UserEntry userEntry)
{
// don't seem to be using this right now, but might be useful (overall sentiment of entry)
DocumentSentiment documentSentiment = client.AnalyzeSentiment(userEntry.Prompt);
double positiveAmount = 0.0;
double negativeAmount = 0.0;
double neutralAmount = 0.0;
int numSentences = 0;
foreach (var sentence in documentSentiment.Sentences)
{
numSentences = numSentences + 1;
positiveAmount = positiveAmount + sentence.ConfidenceScores.Positive;
negativeAmount = positiveAmount + sentence.ConfidenceScores.Negative;
neutralAmount = positiveAmount + sentence.ConfidenceScores.Neutral;
}
double positivePercentage = positiveAmount / numSentences;
double negativePercentage = negativeAmount / numSentences;
double neutralPercentage = neutralAmount / numSentences;
double[] percentages = { positivePercentage, negativePercentage, neutralPercentage };
return(percentages);
}
//Sentiments
public List <Phrase> SentimentAnalysis(string textInput)
{
List <Phrase> phrases = new List <Phrase>();
if (!String.IsNullOrEmpty(textInput))
{
DocumentSentiment documentSentiment = client.AnalyzeSentiment(textInput);
Console.WriteLine($"Document sentiment: {documentSentiment.Sentiment}\n");
foreach (var sentence in documentSentiment.Sentences)
{
Phrase phrase = new Phrase();
phrase.Id = MongoDB.Bson.ObjectId.GenerateNewId().ToString();
Console.WriteLine($"\tText: \"{sentence.Text}\"");
phrase.PhraseText = sentence.Text;
Console.WriteLine($"\tSentence sentiment: {sentence.Sentiment}");
phrase.Sentiment = sentence.Sentiment.ToString();
phrase.Lenght = sentence.Text.Length;
Console.WriteLine($"\tPositive score: {sentence.ConfidenceScores.Positive:0.00}");
phrase.PositiveScore = sentence.ConfidenceScores.Positive;
Console.WriteLine($"\tNegative score: {sentence.ConfidenceScores.Negative:0.00}");
phrase.NegativeScore = sentence.ConfidenceScores.Negative;
Console.WriteLine($"\tNeutral score: {sentence.ConfidenceScores.Neutral:0.00}\n");
phrase.NeutralScore = sentence.ConfidenceScores.Neutral;
phrase.Language = LanguageDetection(phrase.PhraseText);
phrase.NamedEntities = EntityRecognition(phrase.PhraseText);
phrase.KeyPhrases = KeyPhraseExtraction(phrase.PhraseText);
phrases.Add(phrase);
}
}
return(phrases);
}
public static string AnalyzeSentiment(string feedback)
{
var client = new TextAnalyticsClient(endpoint, credentials);
// You will implement these methods later in the quickstart.
DocumentSentiment documentSentiment = client.AnalyzeSentiment(feedback);
return(documentSentiment.Sentiment.ToString());
}
static string SentimentDetection(TextAnalyticsClient client, string textToAnalyze)
{
string sentimentLabel = "negative";
DocumentSentiment documentSentiment = client.AnalyzeSentiment(textToAnalyze);
sentimentLabel = (documentSentiment.Sentiment.ToString());
return(sentimentLabel);
}
static void Main(string[] args)
{
const string SUBSCRIPTION_KEY = "PONER_LA_CLAVE_AQUI";
const string ENDPOINT = "PONER_EL_ENDPOINT_AQUI";
const string TEXTO = "El viaje por Francia del verano pasado fue genial. Conocimos muchos sitios" +
"(el que más nos gustó fue la Provenza) y a mucha gente. Lo único malo fue el tiempo," +
" bastante lluvioso (sobre todo en Normandía). Muchas gracias a nuestro guía, Pierre Martin.";
TextAnalyticsClient client = new TextAnalyticsClient(new Uri(ENDPOINT), new AzureKeyCredential(SUBSCRIPTION_KEY));
/////////////////////////
//Análisis de opinión (Text Analytics-Sentiment)
/////////////////////////
Console.WriteLine("---Análisis de opinión---");
//Invocamos el método de la API para el análisis de la opinión
DocumentSentiment opinion = client.AnalyzeSentiment(TEXTO, "es");
//Procesamos el resultado
Console.WriteLine($"Opinión general del documento: {opinion.Sentiment}\n");
foreach (SentenceSentiment oracion in opinion.Sentences)
{
Console.WriteLine($"\tOración: \"{oracion.Text}\"");
Console.WriteLine($"\tOpinión de la oración: {oracion.Sentiment}\n");
}
/////////////////////////
//Frases clave (Text Analytics-Key Phrases)
/////////////////////////
Console.WriteLine("---Frases clave---");
//Invocamos el método de la API para extraer frases clave
KeyPhraseCollection frases = client.ExtractKeyPhrases(TEXTO, "es");
//Procesamos el resultado
foreach (string frase in frases)
{
Console.WriteLine(frase);
}
/////////////////////////
//Entidades con nombre (Text Analytics-Named Entity Recognition)
/////////////////////////
Console.WriteLine("---Entidades con nombre---");
//Invocamos el método de la API para extraer las entidades
CategorizedEntityCollection entidades = client.RecognizeEntities(TEXTO, "es");
//Procesamos el resultado
foreach (CategorizedEntity entidad in entidades)
{
Console.WriteLine($"{entidad.Text} - Categoría:{entidad.Category}, Subcategoría:{entidad.SubCategory}");
}
}
/*
* The below method gets the user inputs and lets us know the nature of the feedback
*/
private static void CarryOutTestAnalysis(AzureKeyCredential credentials, Uri endpoint)
{
var client = new TextAnalyticsClient(endpoint, credentials);
Console.WriteLine("Please provide your comments");
var inputText = Console.ReadLine();
DocumentSentiment documentSentiment = client.AnalyzeSentiment(inputText);
Console.WriteLine($"Feedback level: {documentSentiment.Sentiment} feedback\n");
Console.ReadLine();
}
/// <summary>
/// Uses the black magic of Azure to calculate the sentiment of the given string.
/// </summary>
/// <param name="input">The input.</param>
/// <param name="languageHint">A hint as to what language the string is in.</param>
/// <returns>The results of the Sentiment analysis.</returns>
public DocumentSentiment Sentiment(string input, string languageHint)
{
DocumentSentiment result = null;
// If we don't have the supported language, the analysis won't be accurate. Skip it.
if (languageHint.SupportedLanguage())
{
result = _client.AnalyzeSentiment(input, languageHint).Value;
}
return(result);
}
private static TextSentiment GetSentiment(string usertext, ILogger log)
{
AzureKeyCredential credentials = new AzureKeyCredential(Environment.GetEnvironmentVariable("COG_KEY"));
Uri endpoint = new Uri(Environment.GetEnvironmentVariable("COG_EP"));
var client = new TextAnalyticsClient(endpoint, credentials);
log.LogInformation($" gor sentence to analyze: {usertext}");
DocumentSentiment documentSentiment = client.AnalyzeSentiment(usertext);
TextSentiment ts = documentSentiment.Sentiment;
log.LogInformation($"CreateRating:Sentiment Score is: {ts}");
return(ts);
}
public SentimentScore Process(string sentence)
{
var client = new TextAnalyticsClient(_endpoint, _credentials);
DocumentSentiment documentSentiment = client.AnalyzeSentiment(sentence, "it");
return(new SentimentScore
{
Positive = documentSentiment.ConfidenceScores.Positive,
Negative = documentSentiment.ConfidenceScores.Negative,
Neutral = documentSentiment.ConfidenceScores.Neutral
});
}
public static string SentimentScore(string Message)
{
var client = new TextAnalyticsClient(endpoint, credentials);
string inputText = Message;
DocumentSentiment documentSentiment = client.AnalyzeSentiment(inputText);
string responseMessage = $"Document sentiment: {documentSentiment.Sentiment}" +
$"\nText: {documentSentiment.ConfidenceScores.Positive}" +
$"\nText: {documentSentiment.ConfidenceScores.Negative}" +
$"\nText: {documentSentiment.ConfidenceScores.Neutral}";
return(responseMessage);
}
internal override void Analyse(TextAnalyticsClient client)
{
if (!Documents.Any() || Documents.Any(d => d == null))
{
throw new InvalidOperationException("A document to analyse has not been provided");
}
if (string.IsNullOrEmpty(Document.Text))
{
throw new InvalidOperationException("Text has not been set for the Document");
}
Document.SetResults(client.AnalyzeSentiment(Document.Text));
}
public async Task Get_Sentiment_Analysis_Results_Using_TypedHttpClient()
{
var document1 = new Document {
Id = "1", Text = "This is a really negative tweet", Language = "en-gb"
};
var document2 = new Document {
Id = "2", Text = "This is a super positive great tweet", Language = "en-gb"
};
var document3 = new Document {
Id = "3", Text = "This is another really super positive amazing tweet", Language = "en-gb"
};
var result1 = new DocumentAnalysis {
Id = "1", Score = 0
};
var result2 = new DocumentAnalysis {
Id = "2", Score = 0.7
};
var result3 = new DocumentAnalysis {
Id = "3", Score = 0.9
};
var documents = new List <Document> {
document1, document2, document3
};
var results = new AnalysisResult {
Documents = new List <DocumentAnalysis> {
result1, result2, result3
}
};
var fakeConfiguration = Substitute.For <IConfiguration>();
var fakeHttpMessageHandler = new FakeHttpMessageHandler(new HttpResponseMessage()
{
StatusCode = HttpStatusCode.OK,
Content = new StringContent(JsonConvert.SerializeObject(results), Encoding.UTF8, "application/json")
});
var fakeHttpClient = new HttpClient(fakeHttpMessageHandler);
var sut = new TextAnalyticsClient(fakeConfiguration, fakeHttpClient);
var result = await sut.AnalyzeSentiment(documents);
result.Documents.Count.ShouldBe(3);
result.Documents.ShouldContain(f => f.Id == result1.Id && f.Score == result1.Score);
}
static void SentimentAnalysisExample(TextAnalyticsClient client)
{
string inputText = "I had the best day of my life. I wish you were there with me.";
DocumentSentiment documentSentiment = client.AnalyzeSentiment(inputText);
Console.WriteLine($"Document sentiment: {documentSentiment.Sentiment}\n");
foreach (var sentence in documentSentiment.Sentences)
{
Console.WriteLine($"\tText: \"{sentence.Text}\"");
Console.WriteLine($"\tSentence sentiment: {sentence.Sentiment}");
Console.WriteLine($"\tPositive score: {sentence.ConfidenceScores.Positive:0.00}");
Console.WriteLine($"\tNegative score: {sentence.ConfidenceScores.Negative:0.00}");
Console.WriteLine($"\tNeutral score: {sentence.ConfidenceScores.Neutral:0.00}\n");
}
}
static void SentimentAnalysisExample(TextAnalyticsClient client)
{
string inputText = "Tive o melhor dia da minha vida. Eu queria que você estivesse lá comigo.";
DocumentSentiment documentSentiment = client.AnalyzeSentiment(inputText, "pt");
Console.WriteLine($"Document sentiment: {documentSentiment.Sentiment}\n");
foreach (var sentence in documentSentiment.Sentences)
{
Console.WriteLine($"\tText: \"{sentence.Text}\"");
Console.WriteLine($"\tSentence sentiment: {sentence.Sentiment}");
Console.WriteLine($"\tPositive score: {sentence.ConfidenceScores.Positive:0.00}");
Console.WriteLine($"\tNegative score: {sentence.ConfidenceScores.Negative:0.00}");
Console.WriteLine($"\tNeutral score: {sentence.ConfidenceScores.Neutral:0.00}\n");
}
}
public SentimentScores ElaborateSentence(string sentence)
{
var client = new TextAnalyticsClient(endpoint, credentials);
DocumentSentiment documentSentiment = client.AnalyzeSentiment(sentence, "it");
Console.WriteLine($"Sentence sentiment: {documentSentiment.Sentiment}\n");
var score = new SentimentScores();
score.SetSentiment((SentimentScores.TextSentiment)documentSentiment.Sentiment);
score.Positive = documentSentiment.ConfidenceScores.Positive;
score.Negative = documentSentiment.ConfidenceScores.Negative;
score.Neutral = documentSentiment.ConfidenceScores.Neutral;
return(score);
}
public Option <DocumentSentiment> DetectSentiment(string text)
{
try
{
_logger.LogInformation("trying to detect sentiment for: {0}", text);
var response = _textAnalyticsClient.AnalyzeSentiment(text);
_logger.LogInformation("sentiment detected: {0}", response.Value.Sentiment);
return(Option <DocumentSentiment> .Some(response.Value));
}
catch (Exception ex)
{
_logger.LogError("can't detect sentiment - ", ex);
return(Option <DocumentSentiment> .None);
}
}
static void SentimentAnalysisExample(TextAnalyticsClient client)
{
string inputText = "The FitnessGram PACER Test is a multistage aerobic capacity test that progressively gets more difficult as it continues. The test is used to measure a students aerobic capacity as part of the FitnessGram assessment. Students run back and forth as many times as they can, each lap signaled by a beep sound. The test get progressively faster as it continues until the student reaches their max lap score.";
DocumentSentiment documentSentiment = client.AnalyzeSentiment(inputText);
Console.WriteLine($"Document sentiment: {documentSentiment.Sentiment}\n");
foreach (var sentence in documentSentiment.Sentences)
{
Console.WriteLine($"\tText: \"{sentence.Text}\"");
Console.WriteLine($"\tSentence sentiment: {sentence.Sentiment}");
Console.WriteLine($"\tPositive score: {sentence.ConfidenceScores.Positive:0.00}");
Console.WriteLine($"\tNegative score: {sentence.ConfidenceScores.Negative:0.00}");
Console.WriteLine($"\tNeutral score: {sentence.ConfidenceScores.Neutral:0.00}\n");
}
}
static void SentimentAnalysisExample(TextAnalyticsClient client, string inputText)
{
DocumentSentiment documentSentiment = client.AnalyzeSentiment(inputText);
Console.WriteLine($"Document sentiment: {documentSentiment.Sentiment}\n");
var si = new StringInfo(inputText);
foreach (var sentence in documentSentiment.Sentences)
{
Console.WriteLine($"\tSentence [length {sentence.GraphemeLength}]");
Console.WriteLine($"\tText: \"{si.SubstringByTextElements(sentence.GraphemeOffset, sentence.GraphemeLength)}\"");
Console.WriteLine($"\tSentence sentiment: {sentence.Sentiment}");
Console.WriteLine($"\tPositive score: {sentence.ConfidenceScores.Positive:0.00}");
Console.WriteLine($"\tNegative score: {sentence.ConfidenceScores.Negative:0.00}");
Console.WriteLine($"\tNeutral score: {sentence.ConfidenceScores.Neutral:0.00}\n");
}
}
public static DocumentSentiment GetSentiment(string input)
{
var client = new TextAnalyticsClient(endpoint, credentials);
DocumentSentiment documentSentiment = client.AnalyzeSentiment(input);
Console.WriteLine($"Document sentiment: {documentSentiment.Sentiment}\n");
var si = new StringInfo(input);
foreach (var sentence in documentSentiment.Sentences)
{
Console.WriteLine($"\tSentence [length {sentence.GraphemeLength}]");
Console.WriteLine($"\tText: \"{si.SubstringByTextElements(sentence.GraphemeOffset, sentence.GraphemeLength)}\"");
Console.WriteLine($"\tSentence sentiment: {sentence.Sentiment}");
Console.WriteLine($"\tPositive score: {sentence.ConfidenceScores.Positive:0.00}");
Console.WriteLine($"\tNegative score: {sentence.ConfidenceScores.Negative:0.00}");
Console.WriteLine($"\tNeutral score: {sentence.ConfidenceScores.Neutral:0.00}\n");
}
return documentSentiment;
}
public void AnalyzeSentiment()
{
string endpoint = Environment.GetEnvironmentVariable("TEXT_ANALYTICS_ENDPOINT");
string subscriptionKey = Environment.GetEnvironmentVariable("TEXT_ANALYTICS_SUBSCRIPTION_KEY");
// Instantiate a client that will be used to call the service.
var client = new TextAnalyticsClient(new Uri(endpoint), subscriptionKey);
string input = "That was the best day of my life!";
Debug.WriteLine($"Analyzing sentiment for input: \"{input}\"");
var sentiment = client.AnalyzeSentiment(input).Value;
Debug.WriteLine($"Sentiment was {sentiment.SentimentClass.ToString()}, with scores: ");
Debug.WriteLine($" Positive score: {sentiment.PositiveScore:0.00}.");
Debug.WriteLine($" Neutral score: {sentiment.NeutralScore:0.00}.");
Debug.WriteLine($" Negative score: {sentiment.NeutralScore:0.00}.");
}
static void SentimentAnalysisExample(TextAnalyticsClient client)
{
string inputText = "I had the best day of my life. I wish you were there with me.";
DocumentSentiment documentSentiment = client.AnalyzeSentiment(inputText);
Console.WriteLine($"Document sentiment: {documentSentiment.Sentiment}\n");
var si = new StringInfo(inputText);
foreach (var sentence in documentSentiment.Sentences)
{
Console.WriteLine($"\tSentence [offset {sentence.Offset}, length {sentence.Length}]");
Console.WriteLine($"\tText: \"{si.SubstringByTextElements(sentence.Offset, sentence.Length)}\"");
Console.WriteLine($"\tSentence sentiment: {sentence.Sentiment}");
Console.WriteLine($"\tPositive score: {sentence.SentimentScores.Positive:0.00}");
Console.WriteLine($"\tNegative score: {sentence.SentimentScores.Negative:0.00}");
Console.WriteLine($"\tNeutral score: {sentence.SentimentScores.Neutral:0.00}\n");
}
}
// build a overall email sentiment, some scoring could be done also
static void SentimentAnalysis(TextAnalyticsClient client, string textSource)
{
DocumentSentiment documentSentiment = client.AnalyzeSentiment(textSource);
Console.WriteLine($"\n\tDocument sentiment: {documentSentiment.Sentiment}\n");
_overallSentiment = documentSentiment.Sentiment.ToString();
foreach (var sentence in documentSentiment.Sentences)
{
double _positive = sentence.ConfidenceScores.Positive;
double _negative = sentence.ConfidenceScores.Negative;
double _neutral = sentence.ConfidenceScores.Neutral;
double[] sentiments = new double[] { _positive, _negative, _neutral };
double maxValue = sentiments.Max();
double maxIndex = sentiments.ToList().IndexOf(maxValue);
Console.Write($"\tResult: \"{maxIndex + " "+ maxValue}\" ");
}
Console.WriteLine();
}
