This repository contains a Python script designed to filter male and female names from a list of Telegram data. The script works by analyzing names (from usernames or first names) and categorizing them based on common gender-specific patterns.
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Name-Based Filtering: The script filters names into male and female categories based on common patterns in names. Heuristic-Based Logic: Uses name prefixes and gender-related keywords to determine the likely gender. Customizable: You can easily modify the name lists and keywords to improve accuracy. Simple and Efficient: Quickly processes large datasets for better organization.
Extract Names: The script works on a dataset that includes first names or usernames. This data can be obtained from Telegram or any other source. Apply Gender Logic: It uses heuristic rules based on common male and female names or prefixes. For example: Male Names: Names like "John," "David," or prefixes like "Mr." Female Names: Names like "Sarah," "Emma," or prefixes like "Ms." Filter and Categorize: The script categorizes the names into male and female lists.
Targeted Messaging: Ideal for personalized marketing campaigns based on gender. Data Analysis: Helps analyze the gender distribution in Telegram name datasets. Event Planning: Organize communication lists for events and promotions based on gender-specific names. Data Management: Makes managing large datasets easier by separating male and female names.