The user must indicate a user name to analyze its toxicity.

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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 Username Toxicity Detection API is a powerful tool that employs natural language processing and machine learning algorithms to assess the potential toxicity or offensiveness of usernames used on online platforms.

The Check user endpoint returns a JSON object containing the analyzed username, a toxicity score, and detailed information about the toxicity categories identified.

The key fields in the response data include "username," which shows the analyzed username, "toxic," indicating the toxicity level (1 for toxic, 0 for non-toxic), and "details," which provides specific categories of toxicity.

The response data is structured as a JSON object. It includes the username as a string, a toxicity score as an integer, and a "details" object that outlines the exact toxicity and its categories.

The Check user endpoint accepts a single parameter: the username to be analyzed. Users must provide this parameter in their POST request.

Users can utilize the returned data by checking the "toxic" field to determine if a username is offensive. The "details" field can help identify specific issues, allowing for targeted moderation actions.

Typical use cases include filtering usernames during registration on social media, moderating discussions in online forums, and ensuring safe gaming environments by blocking toxic usernames.

Data accuracy is maintained through advanced machine learning algorithms that continuously learn from user interactions and feedback, ensuring that the toxicity assessments improve over time.

Quality checks include regular updates to the underlying models, validation against community standards, and user feedback mechanisms to refine the toxicity detection process.

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