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.

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website

Social

OpenChat

# OpenChat Message reaction count Methodology

## 1. Overview

The message reaction count metric measures the daily number of reactions added to messages on the OpenChat social platform. This metric tracks user engagement by counting how many times users react to messages each day. The calculation aggregates `reaction_added` events from OpenChat's event logs, providing insight into the level of interactive engagement within the platform's social ecosystem.

## 2. Data sources

- **OpenChat event logs**: Structured event data from the OpenChat social platform running on Internet Computer blockchain, containing user interaction events with timestamps, event types, user identifiers, and event payloads
- **Platform interaction data**: OpenChat application events that capture all user activities including message reactions, posts, and other social interactions

## 3. Step-by-step calculation

### Component A: Event data preparation
- **Purpose**: Clean and deduplicate raw OpenChat event data to ensure accurate counting
- **Logic**: Raw OpenChat event logs are processed to remove duplicate events. Deduplication is performed by identifying unique combinations of `timestamp`, `user`, event `name`, `source`, and `payload` content. When multiple identical events exist, only the first occurrence is retained using row numbering logic
- **Key fields**: `timestamp` (event occurrence time), `name` (event type identifier), `user` (user performing the action), `source` (event source), `payload` (event-specific data)

### Component B: Reaction event filtering and aggregation
- **Purpose**: Identify message reaction events and aggregate them by day
- **Logic**: From the deduplicated event data, only events with `name` equal to `reaction_added` are selected, representing instances when users add reactions to messages. These filtered events are then grouped by day using timestamp truncation to daily boundaries. The total count of reaction events per day is calculated using a count aggregation
- **Key fields**: `timestamp` (truncated to day), `message_reaction_count` (daily count of reaction events)

### Final aggregation
- **Combining components**: The daily reaction counts are structured with standard metric metadata including business segment classification as `social`, market sector as `social`, and chain identifier as `internetcomputer`
- **Time aggregation**: Events are aggregated to daily boundaries using timestamp truncation, ensuring all reactions within a 24-hour period are counted together
- **Gap filling**: Missing days are filled with zero values to maintain continuous time series data
- **Final calculation**: The final metric value is the total count of `reaction_added` events per day, representing the number of message reactions added by all users on the OpenChat platform each day

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

OpenChatCHAT

Message reaction count

Message reaction count

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