Gender Identification by text API

The Gender Identification by text API accurately predicts authors' genders from text, facilitating personalized marketing, content analysis, and demographic research applications.

About the API:  

The Gender Identification by text API designed to accurately determine the gender of an author based on a fragment of text. In today's digital landscape, where text-based communication is prevalent across various platforms and industries, understanding the demographic characteristics of authors can be valuable for personalized marketing, content analysis, and demographic research. This API serves as a powerful solution for users looking to analyze text data and gain insights into the gender distribution of authors.

Basically, the Gender Identification by text API offers a variety of functionalities to meet the diverse needs of users in different sectors. The main function of the API is to analyze a fragment of text and identify the gender of the author associated with that text. Users can enter text from various sources, such as social media posts, blog articles, customer reviews, or any other written content, and receive the author's intended genre as a result.

The API uses advanced natural language processing (NLP) algorithms and machine learning models trained on extensive data sets to accurately infer the author's gender from the provided text. By analyzing linguistic patterns, writing style, vocabulary, and other linguistic features, the API can distinguish between male and female authors with a high degree of accuracy.

Overall, the Gender Identification by text API serves as a valuable resource for companies, researchers, marketers, and developers looking to analyze text data and gain insights into the gender distribution of authors. By accurately identifying the gender of text authors, this API allows users to make data-driven decisions, improve personalization efforts, and better understand their target audience. Whether used for marketing segmentation, content analysis, or user personalization, the Gender Identification by text API allows users to unlock new opportunities for engagement and growth in today's digital landscape.

 

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. Marketing segmentation: Identify the gender of authors to tailor marketing campaigns and messages based on demographic characteristics.

    Content Analysis: Analyze the gender distribution of authors to understand audience demographics and preferences.

    Customer Feedback Analysis: Determine the gender of authors providing feedback to inform product or service improvements.

    Social Media Analysis – Analyze the gender of authors posting on social media platforms to gain insight into audience and engagement strategies.

    Sentiment Analysis: Incorporate genre identification to understand how sentiment varies between different genres in text data.

     

Are there any limitations to your plans?

Besides the number of API calls available for the plan, there are no other limitations.

 

API Documentation

Endpoints


To use this endpoint you must indicate a text.



                                                                            
POST https://www.zylalabs.com/api/3519/gender+identification+by+text+api/3859/gender+detection
                                                                            
                                                                        

Gender detection - Endpoint Features

Object Description
Request Body [Required] Json
Test Endpoint

API EXAMPLE RESPONSE

       
                                                                                                        
                                                                                                                                                                                                                            {"labelName":"Female","labelId":"label_h311ehjjcp0lbdai","confidence":0.8732972717475144}
                                                                                                                                                                                                                    
                                                                                                    

Gender detection - CODE SNIPPETS


curl --location --request POST 'https://zylalabs.com/api/3519/gender+identification+by+text+api/3859/gender+detection' --header 'Authorization: Bearer YOUR_API_KEY' 

--data-raw '{
    "data": "Hi! I recently visited your website and your makeup products are amazing"
}'

    

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 Gender Identification by text API REST 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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Gender Identification by text API FAQs

To use this API, users must indicate a text and can identify the genre associated with the text.

The Text Gender Identification API parses text input and predicts the gender of the author associated with the text.

There are different plans to suit all tastes, including a free trial for a small number of requests, but your rate is limited to avoid 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 API returns a JSON object containing the predicted gender of the author, a confidence score indicating the accuracy of the prediction, and a unique label ID for the gender classification.

The key fields in the response data include "labelName" (the predicted gender), "labelId" (a unique identifier for the gender), and "confidence" (a numerical value representing the prediction's accuracy).

The primary parameter for the endpoint is the "text" input, which should be a fragment of text from which the API will infer the author's gender.

The response data is structured as a JSON object with three main fields: "labelName," "labelId," and "confidence," allowing users to easily access and interpret the results.

The API utilizes advanced natural language processing algorithms and machine learning models trained on extensive datasets, which include diverse text samples to enhance accuracy in gender prediction.

Data accuracy is maintained through continuous training of machine learning models on updated datasets, ensuring that the API adapts to evolving language patterns and writing styles.

Typical use cases include marketing segmentation, content analysis, customer feedback analysis, social media insights, and sentiment analysis, helping organizations tailor their strategies based on gender demographics.

If the API returns a low confidence score or an empty result, users should consider providing more context or a longer text fragment to improve the accuracy of the gender prediction.

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