public static async Task <IList <SentimentResult> > Analyse(string[] sentences)
{
using (var client = new HttpClient())
{
client.BaseAddress = new Uri(BaseUrl);
// Request headers.
client.DefaultRequestHeaders.Add("Ocp-Apim-Subscription-Key", AccountKey);
client.DefaultRequestHeaders.Accept.Add(new MediaTypeWithQualityHeaderValue("application/json"));
var input = new SentimentInput();
for (int i = 0; i < sentences.Count(); i++)
{
input.Documents.Add(new Document()
{
Id = i + 1, Text = sentences[i]
});
}
// Request body. Insert your text data here in JSON format.
byte[] byteData = Encoding.UTF8.GetBytes(JsonConvert.SerializeObject(input));
// Detect sentiment:
var uri = "text/analytics/v2.0/sentiment";
var response = await CallEndpoint(client, uri, byteData);
var output = JsonConvert.DeserializeObject <SentimentOutput>(response);
return(GenerateResult(input, output));
}
}
public Sentiment GetSentiment(string text)
{
var input = new SentimentInput
{
Text = text
};
var prediction = predictionEnginePool.Predict(modelName: "SentimentAnalysisModel", example: input);
var confidence = prediction.Prediction == "0" ? prediction.Score[0] : prediction.Score[1];
if (confidence < 0.7)
{
return(Sentiment.Neutral);
}
return((prediction.Prediction == "1") ? Sentiment.Positive : Sentiment.Negative);
}
private static IList <SentimentResult> GenerateResult(SentimentInput inputs, SentimentOutput outputs)
{
var ret = new List <SentimentResult>();
foreach (var input in inputs.Documents)
{
foreach (var output in outputs.Documents)
{
if (input.Id == output.Id)
{
ret.Add(new SentimentResult()
{
Sentence = input.Text, SentimentScore = output.Score
});
}
}
}
return(ret);
}