Rolf Tesmer has a demo app showing what Azure Cognitive Services Text Analytics can do:
Each execution of the application on any input file will generate 3 text output files with the results of the assessment. The application runs at a rate of about 1-2 calls per second (the max send rate cannot exceed 100/min as this is the API limit).
File 1 [AzureTextAPI_SentimentText_YYYYMMDDHHMMSS.txt] – the sentiment score between 0 and 1 for each individual line in the Source Text File. The entire line in the file is graded as a single data point. 0 is negative, 1 is positive.
File 2 [AzureTextAPI_SentenceText_YYYYMMDDHHMMSS.txt] – if the “Split Document into Sentences” option was selected then this contains each individual sentence in each individual line with the sentiment score of that sentence between 0 and 1. 0 is negative, 1 is positive. RegEx is used to split the line into sentences.
File 3 [AzureTextAPI_KeyPhrasesText_YYYYMMDDHHMMSS.txt] – the key phrases identified within the text on each individual line in the Source Text File.
Rolf has also put his code on GitHub, so read on and check out his repo.