Miners process transactions and receive fees from users (supply-side fees).

Dogecoin is a distributed ledger for transfer and store of value (a blockchain). Dogecoin was founded by Billy Markus & Jackson Palmer and launched in 2013.

DOGE holders own and govern the protocol. They currently do not take a cut of the total transaction fees paid by users (revenue).

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Blockchains (L1)

Dogecoin

# Dogecoin Active addresses (daily) Methodology

## 1. Overview

The Dogecoin daily active addresses metric counts the number of unique addresses that send transactions each day on the Dogecoin blockchain. This metric measures network activity by tracking distinct users who initiate transactions, providing insight into daily usage patterns and network adoption. The calculation uses UTXO (Unspent Transaction Output) resolution to identify sender addresses, since Dogecoin transactions don't directly expose sender information like account-based blockchains.

## 2. Data sources

The calculation relies on the following raw data sources:

- **Dogecoin blockchain transaction data**: Complete transaction records from the Dogecoin blockchain including transaction hashes, block timestamps, and transaction structure
- **Transaction input data**: Input arrays containing references to previous transaction outputs being spent, including transaction ID (`txid`) and output index (`vout`) fields
- **Transaction output data**: Output arrays containing recipient information and scriptPubKey data with address information
- **Script public key addresses**: Address data embedded in transaction outputs' `scriptPubKey.addresses` JSON fields that identify receiving addresses

## 3. Step-by-step calculation

### Component A: Address resolution lookup table
- **Purpose**: Creates a mapping from transaction outputs to user addresses since UTXO-based blockchains require resolution of spending addresses
- **Logic**: Processes all Dogecoin transaction outputs and extracts the first address from each output's `scriptPubKey.addresses` JSON array. When multiple addresses exist in the array, only the first one is used. Creates a lookup table that maps each unique combination of `transaction_hash` and `output_index` to the corresponding `user_address`. This lookup table enables resolution of sender addresses when those outputs are later spent as inputs in other transactions.
- **Key fields**: `transaction_hash`, `output_index`, and `user_address` for address resolution mapping

### Component B: Historical user identification (pre-2019)
- **Purpose**: Identifies unique user addresses that sent transactions before January 1, 2019, processed as a separate historical dataset for performance optimization
- **Logic**: Extracts input arrays from raw Dogecoin transactions before 2019-01-01, parses each input to extract the referenced `txid` and `vout` fields, then joins with the address resolution lookup table to identify the actual user addresses spending those outputs. Groups results by daily timestamps to create daily user address sets. Uses distinct aggregation to handle cases where the same address appears multiple times per day.
- **Key fields**: `timestamp` (daily truncated), `user_address` resolved from input references

### Component C: Recent user identification (2019 onwards)
- **Purpose**: Identifies unique user addresses that sent transactions from January 1, 2019 onwards, using incremental processing for efficiency
- **Logic**: Follows identical logic to the historical component but processes transactions from 2019-01-01 forward. Extracts transaction inputs, parses `txid` and `vout` references, joins with the address resolution lookup table to identify sender addresses, and aggregates by daily timestamps. Uses incremental processing strategy to efficiently handle new transaction data as it arrives.
- **Key fields**: `timestamp` (daily truncated), `user_address` resolved from input references

### Component D: User DAU base metric creation
- **Purpose**: Combines historical and recent user data into a unified daily active user dataset
- **Logic**: Unions the historical and recent user identification results to create a complete time series of daily active user addresses. Each record represents a user address active on a specific day, labeled with chain identifier 'dogecoin' and user type 'Transaction sender'. No product ID segmentation is applied since this is a chain-level metric.
- **Key fields**: `timestamp`, `chain` (always 'dogecoin'), `user_type` (always 'Transaction sender'), `user_address`

### Component E: HyperLogLog aggregation
- **Purpose**: Efficiently counts distinct user addresses per day using probabilistic data structures to handle large datasets
- **Logic**: Creates HyperLogLog sketches with precision 15 for each combination of timestamp, chain, user type, and product ID. HyperLogLog enables approximate distinct counting with controlled memory usage, essential for blockchain-scale data. Aggregates these sketches across multiple dimensional breakdowns including overall project level, chain level, user type level, and product ID level using sketch merging operations.
- **Key fields**: `timestamp`, `dimensions` (breakdown type), `chain_id`, `user_type`, `product_id`, and `user_dau` (extracted distinct count)

### Final aggregation
- **Combining components**: The HyperLogLog sketches are merged using `hll_count.merge_partial()` and the distinct counts are extracted using `hll_count.extract()` to produce final daily active user counts across all dimensional breakdowns
- **Currency conversion**: No currency conversion required as this is an address count metric, not a value-based metric
- **Time aggregation**: Data is aggregated at daily boundaries using timestamp truncation to day level, ensuring consistent daily reporting periods
- **Final calculation**: The daily active addresses metric is derived by taking the distinct user DAU count and renaming it to `active_addresses_daily`. Missing days are filled with zero values using the finalization macro, and chain availability filtering is applied to ensure data quality and consistency across the time series.

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

Unique active addresses over a fixed 24-hour window.

DogecoinDOGE

Active addresses (daily)

Active addresses (daily)

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