OpenChat users can send messages to each other containing tokens such as ICP. Users can upgrade to Diamond membership to have access to extra or enhanced features.

OpenChat is a chat application running end-to-end on the Internet Computer blockchain.

CHAT tokenholders own and govern the protocol.

github

twitter

website

Social

OpenChat

# OpenChat User registration count Methodology

## 1. Overview

The OpenChat user registration count metric measures the daily number of new users signing up to the OpenChat social platform on the Internet Computer blockchain. This metric tracks user acquisition by counting unique `user_registered` events emitted by the OpenChat application and aggregating them by day. The metric provides insight into user growth patterns and platform adoption trends for this decentralized social networking application.

## 2. Data sources

The calculation relies on the following data sources:
- **OpenChat application events**: Event logs from the OpenChat social platform on Internet Computer containing user interactions and system events
- **Event metadata**: Structured JSON payloads containing user registration details including referral status and bot detection flags  
- **Timestamp data**: Event timestamp information enabling temporal aggregation and daily boundary calculations

## 3. Step-by-step calculation

### Component A: Event deduplication
- **Purpose**: Remove duplicate events from raw OpenChat event stream to ensure accurate counting
- **Logic**: Raw OpenChat events are deduplicated by creating a unique key combining `timestamp`, `user`, event `name`, `source`, and JSON-serialized `payload` content. A row number is assigned using a window function partitioned by these fields, and only the first occurrence of each unique event combination is retained.
- **Key fields**: Event `timestamp`, `user` identifier, event `name`, data `source`, and structured `payload` containing event metadata

### Component B: Registration event filtering  
- **Purpose**: Isolate user registration events from the broader event stream
- **Logic**: Filter the deduplicated events to only include records where the event `name` equals 'user_registered'. Parse the JSON `payload` to extract registration metadata including the `referred` field (indicating if the user was referred by another user) and `is_bot` field (flagging potential bot accounts).
- **Key fields**: Event `name` for filtering, `referred` boolean flag, and `is_bot` detection flag extracted from JSON payload

### Final aggregation
- **Combining components**: Registration events are aggregated by truncating timestamps to daily boundaries using day-level timestamp truncation
- **Currency conversion**: Not applicable for this count-based metric
- **Time aggregation**: Events are grouped by day with timestamp truncation to daily boundaries. Each day's registration count represents all `user_registered` events occurring within that 24-hour period
- **Final calculation**: Count all unique user registration events per day using a simple count aggregation. The metric includes standard metadata fields (`social` market sector, `internetcomputer` chain identifier) and applies a forward-fill strategy with zeros to ensure complete daily coverage without gaps in the time series

*This methodology was automatically generated by Token Terminal's methodology analyzer.*

OpenChatCHAT

User registration count

User registration count

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