Username Toxicity Detection API

API ID 2628

"The Username Toxicity Detection API safeguards online communities by identifying and flagging toxic or offensive usernames in real time."

100% uptime 188 ms avg response

API Documentation

Endpoints

Request

To use this endpoint you must enter a user name.

Endpoint ID: 2642
POST https://zylalabs.com/api/2628/username+toxicity+detection+api/2642/check+user
INPUT PARAMETERS

Check user — Endpoint Features

Object Description
Request Body Required Json

Free test requests remaining: 3 of 3.


INPUT PARAMETERS

API EXAMPLE RESPONSE
JSON
{"username": "jackass1", "result": {"toxic": 1, "details": {"en": {"exact": 1, "categories": ["offensive"]}}}}
Check user — CODE SNIPPETS

curl --location --request POST 'https://zylalabs.com/api/2628/username+toxicity+detection+api/2642/check+user' --header 'Authorization: Bearer YOUR_API_KEY' 

--data-raw '{
    "username": "jackass1",
    "lang": [
        "en"
    ]
}'

    

API Access Key & Authentication

After signing up, every developer is assigned a personal API access key, a unique combination of letters and digits provided to access to our API endpoint. To authenticate with the Username Toxicity Detection API simply include your bearer token in the Authorization header.

Headers
Header Description
Authorization Required Should be Bearer access_key. See "Your API Access Key" above when you are subscribed.

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Overview

About the API:  

The Username Toxicity Detection API is an essential tool for online platforms, social networks and community websites to maintain a safe and welcoming digital environment. This API uses advanced natural language processing and machine learning algorithms to analyze usernames and assess their potential toxicity or offensiveness. It is a critical component in content moderation strategies aimed at preventing harassment, hate speech and inappropriate usernames from infiltrating online communities.

In essence, the Username Toxicity Detection API provides a comprehensive solution to automatically evaluate usernames and flag those that may violate community guidelines or terms of service. This proactive approach to content moderation helps protect users from offensive or harmful usernames, fostering a more positive and inclusive online experience.

Integrating Username Toxicity Detection API into your platform or application is a simple and easy-to-use process. This API has been designed with ease of integration in mind, allowing users, content moderators and platform administrators to seamlessly incorporate its powerful toxicity screening capabilities without major technical hurdles.

In summary, the Username Toxicity Detection API is a vital tool for online platforms and communities that aim to maintain a safe and welcoming digital environment. Its advanced machine learning capabilities and real-time assessment enable content moderation teams to effectively identify and address toxic usernames, ensuring that users can interact and engage online without encountering offensive or harmful content. By integrating this API into their platforms, organizations can take proactive steps to mitigate toxicity and improve the overall user experience, ultimately building more respectful and inclusive online communities.

What this API receives and what your API provides (input/output)?

It will receive parameters and provide you with a JSON.

 

What are the most common uses cases of this API?

  1. Social media platforms: Detect and block toxic usernames during user registration to maintain a safe environment.

  2. Online forums: Automatically filter out offensive usernames to promote respectful discussions.

  3. Gamer communities: Ensure that players adopt non-offensive usernames to create a positive gaming experience.

  4. E-commerce websites: Avoid the use of harmful usernames on e-commerce platforms, improving the online shopping experience.

  5. Dating applications: Test usernames for toxicity to improve the safety and well-being of users.

Are there any limitations to your plans?

Besides the number of API calls, there is no other limitation.

Username Toxicity Detection API FAQs

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

There are different plans suits everyone including a free trial for small amount of requests, but it’s rate is limit to prevent abuse of the service.

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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