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 Video call count Methodology

## 1. Overview

The OpenChat video call count metric measures the daily number of video calls initiated on the OpenChat social platform running on the Internet Computer blockchain. This metric tracks user engagement with video communication features by counting specific message events that represent video call initiations. The calculation aggregates these events daily to provide insights into the platform's video communication usage patterns.

## 2. Data sources

- **OpenChat platform event logs**: Native event tracking system from the OpenChat decentralized social platform on Internet Computer that captures all user interactions and platform activities
- **Message event data**: Structured event records containing timestamps, user identifiers, event types, and JSON payloads with detailed message metadata
- **User activity tracking**: Platform-generated logs that record when users initiate various types of communications including video calls

## 3. Step-by-step calculation

### Component A: Event deduplication
- **Purpose**: Clean and deduplicate raw OpenChat event data to ensure accurate counting
- **Logic**: Raw event logs are processed to remove duplicate entries that may occur due to system retries or logging redundancy. Events are partitioned by `timestamp`, `user` identifier, event `name`, `source`, and JSON `payload` content. Only the first occurrence of each unique event combination is retained using row numbering
- **Key fields**: `timestamp` (event occurrence time), `name` (event type identifier), `user` (user performing the action), `source` (event origin), `payload` (JSON containing event details)

### Component B: Message event parsing  
- **Purpose**: Extract and structure message-specific data from generic event logs
- **Logic**: Filter deduplicated events to include only those where the event `name` equals 'message_sent', indicating a message or communication event. Parse the JSON `payload` to extract structured fields including `chat_id`, `chat_type`, `length`, `message_type`, `sender_is_bot`, and `thread` information. This transforms generic events into structured message records
- **Key fields**: `message_type` (type of message sent), `chat_id` (chat identifier), `user_address` (sending user), `timestamp` (when message was sent)

### Component C: Video call filtering and counting
- **Purpose**: Identify and count video call initiation events
- **Logic**: Filter parsed message events to include only those where `message_type` equals 'VideoCall', which indicates a user initiated a video call. Group these filtered events by day using timestamp truncation to daily granularity. Count the total number of video call events per day
- **Key fields**: `message_type` filtered to 'VideoCall', daily-truncated `timestamp`, `video_call_count` (daily count)

### Final aggregation
- **Combining components**: The pipeline flows linearly from raw event deduplication through message parsing to video call filtering, with each component feeding directly into the next
- **Currency conversion**: Not applicable for this count-based metric
- **Time aggregation**: Events are grouped by calendar day using timestamp truncation, ensuring all video calls within a 24-hour period are counted together
- **Final calculation**: The metric value is the simple count of video call initiation events per day, with additional metadata including 'social' market sector classification, 'internetcomputer' chain identifier, and gap-filling with zero values for days with no video calls to maintain consistent daily reporting

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

OpenChatCHAT

Video call count

Video call count

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