Full-Stack dashboard for Telegram analytics (React, Node.js)
Full-stack application (SPA) for Telegram channel analytics. The system automatically detects abnormal spikes in audience interest and finds viral publications at early stages, using the relative metric Share Rate (repost rate).
A custom parser based on MTProto API (GramJS) has been developed, which collects message history on behalf of the user, bypassing the limitations of the standard Bot API. The core of the system calculates the baseline norm (Median) for each channel using a sliding data window (from T-8 to T-1 days), strictly filtering out informational noise and false anomalies.
Key features:
Smart virality math: The algorithm compares fresh posts not by the number of views, but by the deviation of the repost percentage from the historical norm of a specific channel.
Safe parsing (Anti-Flood): A complex system for bypassing Telegram API blocks has been implemented (floating Jitter delays, pauses during pagination), simulating the behavior of a live person.
Lazy Media Download: To optimize disk space and reduce network load, media files are downloaded and cached by the backend only for confirmed viral posts.
Fault-tolerant database: Using SQLite in asynchronous logging mode (WAL) allows hundreds of records to be written in the background simultaneously and serve data to the frontend without interface freezes.
Autonomous authorization: Native UI input for the Telegram confirmation code directly in the React interface with secure session storage in the database.
Technology stack:
Frontend: React.js, Vite, Tailwind CSS (Dark Mode, Responsive Grid/Table layouts).
Backend: Node.js, Express.js.
API & Data: GramJS (Telegram MTProto Client), better-sqlite3 (WAL mode).
A custom parser based on MTProto API (GramJS) has been developed, which collects message history on behalf of the user, bypassing the limitations of the standard Bot API. The core of the system calculates the baseline norm (Median) for each channel using a sliding data window (from T-8 to T-1 days), strictly filtering out informational noise and false anomalies.
Key features:
Smart virality math: The algorithm compares fresh posts not by the number of views, but by the deviation of the repost percentage from the historical norm of a specific channel.
Safe parsing (Anti-Flood): A complex system for bypassing Telegram API blocks has been implemented (floating Jitter delays, pauses during pagination), simulating the behavior of a live person.
Lazy Media Download: To optimize disk space and reduce network load, media files are downloaded and cached by the backend only for confirmed viral posts.
Fault-tolerant database: Using SQLite in asynchronous logging mode (WAL) allows hundreds of records to be written in the background simultaneously and serve data to the frontend without interface freezes.
Autonomous authorization: Native UI input for the Telegram confirmation code directly in the React interface with secure session storage in the database.
Technology stack:
Frontend: React.js, Vite, Tailwind CSS (Dark Mode, Responsive Grid/Table layouts).
Backend: Node.js, Express.js.
API & Data: GramJS (Telegram MTProto Client), better-sqlite3 (WAL mode).
Odessa 
Available for hire
Offer work