Node operators process transactions and receive token incentives. These independently owned high-spec node machines around the world are connected via Internet Computer Protocol (ICP), creating a self-sovereign network not reliant on any cloud services. Advanced cryptography allows any application or service to be run on the network in a decentralized manner via smart contracts.

The Internet Computer is a decentralized cloud blockchain, where apps can be built fully onchain, using AI, or by coding. Try caffeine.ai & icp.ninja.

ICP tokenholders own and govern the protocol. They currently take (burn) all of the total transaction fees paid by users (revenue). ICP Holders can stake their ICP on the Network Nervous System (NNS), an advanced fully on-chain DAO that facilitates liquid democracy. Staking ICP allows users to submit proposals, vote on proposals, and earn rewards for their participation in governance. Internet Computer's investors include Polychain, Scalar Capital, Amino Capital, etc.

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Blockchains (L1)

Internet Computer

# Internet Computer Active internet identities Methodology

## 1. Overview

Active Internet Identities measures the number of unique users who authenticated through the Internet Computer's Internet Identity system on a daily basis. This metric tracks user engagement and adoption of the Internet Computer ecosystem by counting daily unique logins to the decentralized identity authentication system. The calculation uses scraped data from Internet Computer network infrastructure to extract daily login statistics and formats them into a standardized time series metric.

## 2. Data sources

The calculation relies on the following raw data sources:
- **Internet Computer scraper data**: Daily statistics collected from Internet Computer network infrastructure containing JSON-formatted metrics
- **Internet Identity authentication logs**: Records of user authentication events through the Internet Identity system
- **Network statistics feeds**: Daily aggregated statistics from Internet Computer nodes and infrastructure

## 3. Step-by-step calculation

### Component A: Raw data extraction and parsing
- **Purpose**: Extract daily Internet Identity login counts from scraped JSON data
- **Logic**: The process begins by accessing scraped data from Internet Computer infrastructure that contains nested JSON arrays with daily statistics. The system extracts the `daily_stats` array from the raw JSON data and unnests it to access individual daily records. For each daily record, it parses the `day` field as a timestamp and extracts the `daily_internet_identity_logins` value as the count of active identities. The data is tagged with Internet Computer as the source chain and 'day' as the timestamp granularity. Each record also carries an `inserted_at` timestamp indicating when the data was collected by the scraper.
- **Key fields**: `day` (converted to timestamp), `daily_internet_identity_logins` (the core metric value), `inserted_at` (data collection timestamp)

### Component B: Data versioning and deduplication  
- **Purpose**: Handle multiple data insertions for the same day and select the most recent values
- **Logic**: Since the scraper may collect data multiple times for the same day (due to updates or corrections), the system implements a deduplication strategy. It assigns row numbers to records partitioned by the timestamp (day) and ordered by the insertion timestamp in descending order. This ensures that for any given day, the most recently inserted data point receives row number 1. The system then filters to keep only records with row number 1, effectively selecting the latest available data for each day.
- **Key fields**: `timestamp` (daily boundary), `amount` (processed Internet Identity count), `row_number` (deduplication ranking)

### Component C: Business metadata standardization
- **Purpose**: Apply standardized business categorization and metric formatting
- **Logic**: The processed daily counts are enhanced with standardized business metadata to align with Token Terminal's metric framework. The system adds chain identification as 'internetcomputer', categorizes the business line as 'Blockchain', sets the market sector as 'blockchains_l1', and assigns the business segment as 'blockchain'. The product ID is set to null since this is a network-level metric rather than a specific product metric. The version is marked as 'v1' for tracking methodology versions.
- **Key fields**: `chain_id` (set to Internet Computer), `business_line`, `market_sector_id`, `business_segment_id`, `active_internet_identities` (renamed from amount)

### Final aggregation
- **Combining components**: The components flow sequentially - raw data extraction feeds into deduplication, which feeds into business standardization
- **Currency conversion**: Not applicable as this metric counts users rather than financial values
- **Time aggregation**: Data is aggregated at daily boundaries using the timestamp from the source data, with each day representing the count of unique Internet Identity logins for that 24-hour period
- **Final calculation**: The final metric value is the daily count of unique Internet Identity authentications, processed through a finalization macro that applies a 'fill_zeros' strategy to ensure continuous daily time series data and applies chain availability filters to maintain data quality standards

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

Internet ComputerICP

Active internet identities

Active internet identities

Competitive landscape