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 Message tip count Methodology

## 1. Overview

The OpenChat message tip count metric measures the daily volume of message tipping activity on the OpenChat social messaging platform. This metric quantifies user engagement through the act of tipping messages, where users can show appreciation for content by sending tips. The calculation counts the total number of distinct message tipping events that occur each day on the Internet Computer blockchain, providing insight into the social and economic activity within the OpenChat ecosystem.

## 2. Data sources

The calculation relies on the following data sources:

- **OpenChat event logs**: Raw event data from the OpenChat social messaging platform running on the Internet Computer blockchain
- **Internet Computer blockchain data**: Blockchain event logs and transaction records from the Internet Computer network
- **Platform interaction data**: User activity events including message interactions, tipping events, and social engagement metrics
- **Event metadata**: Timestamps, user identifiers, event classifications, data sources, and event payload information

## 3. Step-by-step calculation

### Component A: Raw event data extraction
- **Purpose**: Extracts and processes raw OpenChat platform events from Internet Computer blockchain logs
- **Logic**: The system collects all user interaction events from the OpenChat platform, including message posts, tips, reactions, and other social activities. Each event contains a `timestamp`, `name` (event type), `user` (identifier), `source` (data origin), and `payload` (additional event data)
- **Key fields**: `timestamp` for event timing, `name` for event classification, `user` for participant identification, `source` for data provenance, `payload` for event-specific data

### Component B: Event deduplication
- **Purpose**: Removes duplicate events to ensure accurate counting of unique tipping activities
- **Logic**: The system identifies potential duplicate events by grouping records with identical `timestamp`, `user`, `name`, `source`, and serialized `payload` values. Within each group, it assigns row numbers and retains only the first occurrence of each unique event combination. This prevents double-counting of the same tipping action due to data processing artifacts or multiple data ingestion processes
- **Key fields**: All event fields used as deduplication keys, with `row_number` for duplicate identification

### Component C: Message tip event filtering
- **Purpose**: Isolates specifically the message tipping events from all OpenChat platform activities
- **Logic**: From the deduplicated event stream, the system filters to retain only events where the `name` field equals `message_tipped`. This captures instances where users have sent tips to reward or appreciate specific messages within the OpenChat platform
- **Key fields**: `name` field used for event type filtering to identify tipping actions

### Final aggregation
- **Combining components**: The filtered message tipping events are aggregated at the daily level by truncating the `timestamp` field to day boundaries
- **Time aggregation**: Events are grouped by day using timestamp truncation, ensuring all tipping activities within a 24-hour period are counted together
- **Final calculation**: The metric value represents the total count of distinct message tipping events per day, calculated using a simple count aggregation of all qualifying events within each daily time bucket. The result shows the daily volume of tipping activity on the OpenChat platform, indicating user engagement and economic activity within the social messaging ecosystem

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

OpenChatCHAT

Message tip count

Message tip count

Competitive landscape