Lessons From Processing Millions of Telegram Messages: What We Learned About Spam

1. 1Collect and analyze large datasets of Telegram messages to identify spam patterns
2. 2Implement a system to re-check edited messages for spam content
3. 3Develop AI-powered anti-spam models that can detect sophisticated spam techniques
4. 4Continuously update and refine the models based on new data and emerging spam patterns

Data scientists and AI engineers on a team can benefit from understanding these patterns to improve their anti-spam systems, while developers can use this knowledge to build more effective Telegram bots

💡 Modern spammers are using sophisticated techniques such as the 'edit trick' to evade detection, highlighting the need for AI-powered anti-spam systems that can detect and adapt to these evolving patterns

💡 Did you know spammers use the 'edit trick' to evade detection? They post normal messages and edit them into scam links later!