> For the complete documentation index, see [llms.txt](https://docs.marketcompass.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.marketcompass.ai/subnet/subnet-17.md).

# Subnet 17

Market Compass utilizes Commune AI, specifically Subnet 17, to gather real-time data from X (Twitter) at scale. Here's how the subnet operates:

1. **Query Creation:**
   * Queries are created to access the X (Twitter) API, targeting market-related topics.
2. **Query Distribution:**
   * Miners within Subnet 17 receive a unique query to perform every minute, just before each voting cycle begins.
3. **Query Validation:**
   * Miners return updates for all queries, ensuring that the data collected is fresh and relevant.
   * Trust is placed in miners by default, assuming they provide accurate and valid data.
4. **Backend Verification:**
   * An undisclosed endpoint in our backend verifies random queries with timestamps provided by miners.
   * If the response differs from the expected data, the miner is blacklisted, ensuring data integrity.
5. **New Miner Validation:**
   * New miners undergo validation checks upon their first request to ensure data accuracy and reliability.
6. **Scoring System:**
   * The scoring system rewards miners for providing valid data, with emission distributed evenly among valid miners.
   * This approach builds a resource base necessary for future development and expansion.