
Overview
Registration Activity
Neuron registration trends

Neuron registration trends
The alpha price in τ, day by day, and what moved it each way.
Log change over the last 30 days −12.70%: protocol buys 0.00%, root sells −0.37%, users net −12.66%, cross-subnet +0.34%, unattributed +0.0004%.
The chart follows the alpha price in τ. Each period starts at its opening price and steps through the mechanisms below, in a fixed order, to its closing price: a step that rises pushed the price up, one that falls pushed it down, and its height is how far it moved the price. A thin line carries each close into the next period’s open; it is dashed where the two differ. The faint candle behind each period is the market’s own open, high, low and close, for context.
With many periods on screen (90 days, or hours), the steps would be too thin to read, so the chart draws the price as a line instead and colours each period by the mechanism that moved it most. Hover a period for the full step-by-step breakdown.
Not here, because they do not move the spot price: the per-block TAO injection into the pool, and burns.
All figures are log changes, not simple percentage changes, so the parts add up exactly to the total; on big moves the two differ (a 10% log fall is a 9.5% price fall).
2026-11-08 UTC, as of ≈18:41 UTC (block 9,463,294)
The day isn’t over yet, so these figures keep changing. They are in no daily total, average or rank.
Organizations conducting market research, trend analysis, and competitive intelligence rely heavily on social media data from X, Reddit, and other platforms. Centralized scraping APIs are expensive, often charge per-request fees, impose rate limits, and require maintaining relationships with individual platform providers. This creates barriers for smaller research teams and startups that need continuous, large-scale data collection.
A decentralized network of data scrapers can distribute collection costs across many contributors, each incentivized to gather and verify high-quality data. By combining independent scrapers with built-in validation mechanisms, the network can operate continuously, scale horizontally, and reduce per-unit data costs while maintaining data quality through cryptographic verification.
Data Universe implements this by recruiting miners to scrape data from X, Reddit, and YouTube, storing it in distributed databases indexed by source, time, and label (hashtag, subreddit, etc.).
Validators periodically retrieve miner data, re-scrape original sources to verify correctness, and score miners based on data freshness, uniqueness across the network, and credibility. Miners earn rewards proportional to the value and volume of verified data they provide.
Auto-generated from the GitHub repository and may not reflect the latest changes.
Data Universe (Subnet 13) is a Bittensor subnet for collecting and storing large amounts of data from social media sources (X/Twitter, Reddit, YouTube) for use by other subnets and businesses. Miners scrape data from these sources and store it in local databases, while validators verify data correctness and score miners based on data freshness, desirability, uniqueness, and credibility.
Data Universe operates as a decentralized data scraping and storage network. Miners scrape data from social media sources (X, Reddit, YouTube) and store it in local SQLite databases, organized into DataEntityBuckets identified by source, time bucket, and label. Miners expose their MinerIndex (summary of data) and DataEntityBuckets via an Axon (request handler) to validators.
Validators periodically: (1) retrieve and cache all miners' MinerIndexes, (2) sample random buckets from each miner, (3) retrieve and verify data correctness by re-scraping original sources, (4) update miner credibility scores, and (5) calculate miner scores based on data value and credibility. Miners can optionally upload data to S3 via presigned URLs for public access. Dynamic Desirability system allows validators to vote on which data labels are desirable, with voting power proportional to stake (validators: 70% total, subnet owner: 30%).
Validators commit their preference votes to Bittensor chain via SHA hashes. Aggregate desirability lookup is reconstructed from chain-committed votes and used for scoring.
Raw score is calculated as: raw_score = data_type_scale_factor × time_scalar × scorable_bytes. Final score incorporates credibility as: final_score = raw_score × (credibility ^ 2.5). Data freshness uses linear deprecation over 30 days.
Desirability is dynamically set by validators voting on label weights. Duplication factor decreases value proportionally to number of miners storing identical data. Miner credibility ranges 0-1, updated via exponential moving average (α=0.15) based on validation checks.
Validators periodically sample and verify data correctness, updating credibility accordingly.
The sections above were auto-generated from the GitHub repository and may not reflect the latest changes. View repository (github.com, opens in a new tab, external site)
Scraping the world's social media data
This information was auto-extracted from the GitHub repository and may be incomplete or out of date. Always refer to the subnet's GitHub repository (github.com, opens in a new tab, external site) for the latest instructions.
Not yet verified: GPU, OS
No GPU required. Low-tier machine sufficient with adequate bandwidth and disk space.
Not yet verified: GPU, CPU cores, OS, Notes
Machine-extracted from the subnet's repository docs; may be wrong or out of date. Check the repository before buying or renting hardware. Open the repository (github.com, opens in a new tab, external site) · Extracted 26 Oct 2026
Clone the Data Universe repository
git clone https://github.com/RusticLuftig/data-universe.git
Setup Python virtual environment or Conda environment
python -m venv data-universe-env && source data-universe-env/bin/activate
Install required dependencies
cd data-universe && python -m pip install -e .
Verify Reddit access before registering (must return 200, not 403)
curl -s -o /dev/null -w "%{http_code}\n" "https://www.reddit.com/r/bitcoin/new.json"Create Bittensor wallet and register hotkey
btcli wallet new_coldkey --wallet.name your-wallet && btcli wallet new_hotkey --wallet.name your-wallet --wallet.hotkey your-hotkey
Start miner using pm2 process manager in online mode
pm2 start python -- ./neurons/miner.py --wallet.name your-wallet --wallet.hotkey your-hotkey
Verify miner is collecting data by checking logs for successful scrapes
pm2 logs <process-name> | grep -i "scrap\|status 403\|status 401"
Clone the Data Universe repository
git clone https://github.com/RusticLuftig/data-universe.git
Setup Python virtual environment or Conda environment
python -m venv data-universe-env && source data-universe-env/bin/activate
Install required dependencies
cd data-universe && python -m pip install -e .
Create Bittensor wallet and register hotkey on the network
btcli wallet new_coldkey --wallet.name your-wallet && btcli wallet new_hotkey --wallet.name your-wallet --wallet.hotkey your-hotkey
Configure environment variables for data scrapers (Apify and/or Reddit)(optional)
# Set up .env file with APIFY_API_TOKEN, REDDIT_CLIENT_ID, REDDIT_CLIENT_SECRET, REDDIT_USERNAME, REDDIT_PASSWORD
Start validator with auto-updates (recommended)
pm2 start --name net13-vali-updater --interpreter python scripts/start_validator.py -- --pm2_name net13-vali --wallet.name cold_wallet --wallet.hotkey hotkey_wallet
Start validator without auto-updates (alternative method)(optional)
pm2 start python -- ./neurons/validator.py --wallet.name your-wallet --wallet.hotkey your-hotkey
| Day (UTC) | Share |
|---|---|
| 2026-11-07 | 0.0004% |
| 2026-11-06 | 0.0005% |
| 2026-11-05 | 0.0004% |
| 2026-11-04 | 0.0005% |
| 2026-11-03 | 0.0005% |
| 2026-11-02 | 0.0005% |
| 2026-11-01 | 0.0005% |
| 2026-10-31 | 0.0005% |
| 2026-10-30 | 0.0005% |
| 2026-10-29 | 0.0005% |
| 2026-10-28 | 0.0005% |
| 2026-10-27 | 0.0005% |
| 2026-10-26 | 0.0005% |
| 2026-10-25 | 0.0005% |
| 2026-10-24 | 0.0005% |
| 2026-10-23 | 0.0006% |
| 2026-10-22 | 0.0006% |
| 2026-10-21 | 0.0006% |
| 2026-10-20 | 0.0006% |
| 2026-10-19 | 0.0006% |
| 2026-10-18 | 0.0006% |
| 2026-10-17 | 0.0006% |
| 2026-10-16 | 0.0007% |
| 2026-10-15 | 0.0007% |
| 2026-10-14 | 0.0007% |
| 2026-10-13 | 0.0007% |
| 2026-10-12 | 0.0008% |
| 2026-10-11 | 0.0008% |
| 2026-10-10 | 0.0007% |
| 2026-10-09 | 0.0008% |
| 2026-10-08 | 0.0008% |
| 2026-10-07 | 0.0008% |
| 2026-10-06 | 0.0009% |
| 2026-10-05 | 0.001% |
| 2026-10-04 | 0.0009% |
| 2026-10-03 | 0.001% |
| 2026-10-02 | 0.0011% |
| 2026-10-01 | 0.0009% |
| 2026-09-30 | 0.0011% |
| 2026-09-29 | 0.0009% |
| 2026-09-28 | 0.0009% |
| 2026-09-27 | 0.0009% |
| 2026-09-26 | 0.0015% |
| 2026-09-25 | 0.0013% |
| 2026-09-24 | 0.0012% |
| 2026-09-23 | 0.0013% |
| 2026-09-22 | 0.0014% |
| 2026-09-21 | 0.0016% |
| 2026-09-20 | 0.0018% |
| 2026-09-19 | 0.0016% |
| 2026-09-18 | 0.0015% |
| 2026-09-17 | 0.0017% |
| 2026-09-16 | 0.002% |
| 2026-09-15 | 0.0018% |
| 2026-09-14 | 0.0018% |
| 2026-09-13 | 0.0017% |
| 2026-09-12 | 0.0017% |
| 2026-09-11 | 0.0016% |
| 2026-09-10 | 0.0017% |
| 2026-09-09 | 0.0022% |
| 2026-09-08 | 0.0022% |
| 2026-09-07 | 0.0021% |
| 2026-09-06 | 0.0024% |
| 2026-09-05 | 0.0028% |
| 2026-09-04 | 0.0027% |
| 2026-09-03 | 0.0027% |
| 2026-09-02 | 0.0024% |
| 2026-09-01 | 0.0021% |
| 2026-08-31 | 0.0022% |
| 2026-08-30 | 0.0022% |
| 2026-08-29 | 0.0025% |
| 2026-08-28 | 0.0026% |
| 2026-08-27 | 0.0027% |
| 2026-08-26 | 0.0026% |
| 2026-08-25 | 0.0028% |
| 2026-08-24 | 0.0023% |
| 2026-08-23 | 0.0021% |
| 2026-08-22 | 0.0025% |
| 2026-08-21 | 0.0029% |
| 2026-08-20 | 0.0028% |
| 2026-08-19 | 0.003% |
| 2026-08-18 | 0.0031% |
| 2026-08-17 | 0.003% |
| 2026-08-16 | 0.0029% |
| 2026-08-15 | 0.0031% |
| 2026-08-14 | 0.0031% |
| 2026-08-13 | 0.0032% |
| 2026-08-12 | 0.0036% |
| 2026-08-11 | 0.0043% |
| 2026-08-10 | 0.0047% |