To use this API, users must enter a text to obtain a sentiment analysis.

Retrieve Emotion Tone Analysis API designed to analyze text data and detect the emotional tone expressed in it.

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Zyla provides a wide range of integration methods for almost all programming languages. You can use these codes to integrate with your project as you need.

The API returns a JSON object containing sentiment analysis results, including overall sentiment, confidence scores, and detailed sentiment for individual sentences.

Key fields include "sentiment" (overall sentiment), "confidence" (certainty of the sentiment), and "sentences" (array detailing sentiment for each sentence with offsets and lengths).

The response is structured as a JSON object with a "document" section for overall sentiment and a "sentences" array for detailed analysis of each sentence.

The endpoint accepts parameters such as "text" (the input text for analysis) and "language" (to specify the language, e.g., 'en' for English or 'de' for German).

The endpoint provides insights into the emotional tone of the text, including sentiment classification (positive, negative, neutral) and confidence levels for both overall and sentence-specific sentiments.

Users can analyze the overall sentiment to gauge customer opinions and use sentence-level data to identify specific areas of concern or positive feedback, aiding in targeted responses.

The API employs natural language processing and machine learning algorithms, continuously trained on diverse datasets to enhance accuracy in sentiment detection.

Common use cases include monitoring social media sentiment, analyzing customer feedback, and assessing brand reputation, helping businesses make informed decisions based on emotional insights.

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