Arbitrum One batches users' transactions and submits them to Ethereum, paying a share of the transaction fees to Ethereum validators (expense).

Arbitrum One is an L2 smart contract platform for decentralized applications on Ethereum. Arbitrum was founded by Offchain Labs and launched in 2021.

ARB tokenholders own and govern the protocol. They currently run the only sequencer and take a cut of the total transaction fees paid by users (revenue). Arbitrum’s investors include Polychain, Alameda Research, Coinbase Ventures, etc.

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Arbitrum One

# Arbitrum One Active addresses (weekly) Methodology

## 1. Overview

Weekly active addresses measures the number of unique addresses that initiated at least one transaction on the Arbitrum blockchain during a 7-day rolling window. This metric provides insights into user engagement and network activity by tracking distinct wallet addresses that actively participate in transactions, regardless of transaction frequency or value. The calculation uses a rolling 7-day window approach with HyperLogLog sketches to efficiently handle large datasets and ensure accurate distinct counting across overlapping time periods.

## 2. Data sources

The calculation relies on the following raw data sources:
- **Arbitrum transaction records**: Complete transaction history from the Arbitrum blockchain, including transaction hashes, timestamps, sender addresses (`from_address`), recipient addresses (`to_address`), and gas-related fields
- **Token metadata**: WETH contract address (`0x82af49447d8a07e3bd95bd0d56f35241523fbab1`) used as a standardized token reference for gas fee calculations
- **Chain availability data**: Configuration data that defines operational periods for the Arbitrum blockchain to filter out data from periods when the chain was not available

## 3. Step-by-step calculation

### Component A: Transaction data extraction
- **Purpose**: Extract and standardize all transaction records from the Arbitrum blockchain
- **Logic**: Pull all distinct transactions from Arbitrum blockchain data, capturing essential fields including block timestamp, transaction hash, sender address (`from_address`), recipient address (`to_address`), gas price, and gas usage. Each transaction is tagged with the WETH contract address as the standard token reference and assigned market sector and business segment identifiers (`blockchains_l2` and `blockchain` respectively). Gas fees are calculated by multiplying gas used amount by gas price and converting from wei to ETH units.
- **Key fields**: `block_timestamp` for timing, `from_address` as the active user identifier, `transaction_hash` for uniqueness, `gas_price` and `gas_used_amount` for fee calculations

### Component B: Daily active user identification  
- **Purpose**: Identify unique active addresses for each day
- **Logic**: Group transaction records by day using timestamp truncation to day granularity. For each day, identify all unique sender addresses (`from_address`) as daily active users. Each record represents one address being active on a specific day, with the user type classified as "Transaction sender" to distinguish from other potential user types in the broader system.
- **Key fields**: `timestamp` truncated to day, `user_dau` containing the unique address, `chain` identifier, `user_type` set to "Transaction sender"

### Component C: Rolling window construction
- **Purpose**: Create 7-day rolling windows for weekly active user calculation
- **Logic**: Generate a complete datespine covering all days from the earliest transaction date to the current date minus one day. For each day in the datespine, create a 7-day lookback window by generating timestamps for that day and the previous 6 days. Join this window structure with the daily active user data to collect all user activity within each 7-day period. Use HyperLogLog sketches to initialize efficient distinct counting structures for each day's user set.
- **Key fields**: `timestamp` for the end date of each window, `joinday` for connecting to historical daily data, `hll` sketches for distinct counting

### Component D: Weekly active user aggregation
- **Purpose**: Calculate weekly active users using HyperLogLog merge operations
- **Logic**: For each 7-day window, merge all HyperLogLog sketches from the constituent days to get an accurate count of distinct users across the entire period. This approach handles cases where the same address is active on multiple days within the window, ensuring each unique address is counted only once. Generate breakdowns across multiple dimensions including chain-level (focusing on Arbitrum), project-level (using the `arbitrum` project tag), user-type level, and product-level aggregations.
- **Key fields**: `user_wau` containing the final distinct user count, `dimensions` indicating the breakdown level, `chain_id` for chain-specific metrics

### Final aggregation
- **Combining components**: Union all dimensional breakdowns (chain, project, user type, product) into a single dataset while maintaining the appropriate grouping structure. Filter to include only chain-level and project-level dimensions for the final active addresses metric.
- **Currency conversion**: Not applicable for this metric as it counts addresses rather than monetary values
- **Time aggregation**: Each record represents a 7-day rolling window ending on the specified date, with daily calculation frequency ensuring continuous coverage
- **Final calculation**: Rename the `user_wau` field to `active_addresses_weekly` to align with the metric naming convention. Apply finalization logic including schema standardization, missing day handling with zero-fill strategy, and chain availability filtering to exclude data from periods when Arbitrum was not operational. The final metric value represents the count of unique addresses that sent at least one transaction during the 7-day period ending on each date.

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

Unique active addresses over a rolling 7-day window.

Arbitrum OneARB

Active addresses (weekly)

Active addresses (weekly)

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