To use this API you must enter a text to get a sentiment analysis.

The Opinion Mining API is a powerful tool based on natural language processing (NLP) that analyzes textual data to determine sentiments, opinions, or emotional tones expressed within the text.

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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 sentiment analysis endpoint returns a JSON object containing sentiment classifications, including lists of negative and positive words, a sentiment score, and an overall verdict (positive, negative, or neutral).

Key fields in the response include "negative" and "positive" arrays for identified words, "score" indicating sentiment strength, "scored_words" for the number of analyzed words, "verdict" for overall sentiment, and "words" for total word count.

The response data is structured as a JSON object with arrays for positive and negative words, numerical values for scores, and string values for verdicts, allowing for easy parsing and analysis in applications.

The primary parameter for the sentiment analysis endpoint is the text input, which should be a string containing the content you want to analyze for sentiment.

Users can customize their requests by varying the input text to analyze different content, such as customer reviews or social media posts, to obtain tailored sentiment insights.

Typical use cases include monitoring social media sentiment, analyzing customer feedback, managing brand reputation, conducting market research, and evaluating product reviews for insights on customer preferences.

Data accuracy is maintained through advanced machine learning algorithms trained on diverse datasets, ensuring the model can effectively interpret various linguistic expressions and contexts.

If the input text is too short or lacks sentiment, the API may return neutral results. Users should ensure the text is sufficiently descriptive to yield meaningful sentiment analysis.

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