The Text Analytics app is part of Azure Cognitive Services. It is a cloud-based service, which includes a collection of machine learning tools and AI algorithms, for the development of intelligent systems. It provides advanced natural language processing over raw text. Text analysis can mean different things, but in Cognitive Services, the Text Analysis Application’s programming interface offers four types of analysis. The four main functions are sentiment analysis, extraction of key phrases, language detection and recognition of named entities.

Sentiment analysis – this feature identifies what consumers think about a particular brand or topic, analyzing the text for tips on negative or positive feelings. Returns a score between 0 and 1 for each document, where 1 is the most positive. Analysis templates are pre-trained using an extensive body of text and natural language technology from Microsoft. For selected languages, the resource analyzes and punctuates any raw text provided, returning the results directly to the calling application.

Key phrase extraction – Automatically extract key phrases to quickly identify key points. For example, for the input text, the food was delicious and there was a wonderful team, the API returns the main points of discussion: food and wonderful team.

Language detection – Detects in which language the input text is written and reports a unique language code for each document sent in the request. It contains a wide variety of languages, variants, dialects, and some regional/cultural languages. The language code is associated with punctuation that indicates its relevance.

Named entity recognition – identifies and categorizes entities in the text such as people, places, organizations, date \ time, quantities, percentages, currencies, and more.

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