01

LIVE LOVE INDEX

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Composite LOVE Index / 1000
Weighted average of all 6 subindices
Network
Base Sepolia (Chain 84532)
Oracle Contract
0x53F0...FcD ↗
Last Refresh
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00 — Global Peace
20%
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Source: NewsAPI / GDELT
01 — Charitable Giving
15%
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Source: NewsAPI / Giving USA
02 — Social Sentiment
20%
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Source: NewsAPI / Twitter
03 — Environmental Care
15%
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Source: NewsAPI / Carbon Monitor
04 — Community Wellness
15%
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Source: NewsAPI / WHO
05 — Good Spend
15%
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Source: On-Chain (Automatic)
02

METHODOLOGY

How the LOVE Index Is Calculated

The LOVE Index is a weighted composite score ranging from 0 to 1000. It is computed entirely on-chain by the SentimentOracle smart contract using this formula:

LOVE = Σ (Scorei × Weighti) / 10,000

Each of the 6 subindices has a score between 0 and 1000 (where 500 = neutral, 0 = extremely negative, 1000 = extremely positive). Weights are expressed in basis points and sum to 10,000.

Subindices 0–4 are updated by the oracle pipeline every 6 hours, pulling real-world data from news APIs and running sentiment analysis. Subindex 5 (Good Spend) updates automatically on-chain when LefCoin is transferred to verified good destinations.

🕊️
00 — Global Peace (20%)

What It Measures

Armed conflicts, peace treaties, diplomatic progress, and global security sentiment.

Data Pipeline

  • GDELT global news: headlines on peace, conflict, war, treaty — 25 most recent articles
  • SerpAPI: Google search results for "global peace index" and conflict resolution
  • Reddit: Community discourse on world peace and geopolitics
  • ReliefWeb: UN OCHA humanitarian situation reports
  • Keyword sentiment analysis (positive/negative word ratio) with optional LLM

Data Sources (Live)

GDELT SerpAPI Reddit ReliefWeb
💝
01 — Charitable Giving (15%)

What It Measures

Global donation volumes, humanitarian aid activity, and charitable sentiment across news and community discourse.

Data Pipeline

  • GDELT global news: headlines on charity, donation, humanitarian, volunteer, giving
  • SerpAPI: Google search results for charitable giving trends and humanitarian aid
  • Reddit: Community discourse on philanthropy, mutual aid, and volunteering
  • ReliefWeb: UN OCHA humanitarian appeals and donation tracking
  • Keyword sentiment analysis (positive/negative word ratio) with optional LLM

Data Sources (Live)

GDELT SerpAPI Reddit ReliefWeb
💬
02 — Social Sentiment (20%)

What It Measures

Overall tone of public discourse across social media, news, and happiness research.

Data Pipeline

  • Hedonometer: Real-time happiness index from Twitter language analysis (University of Vermont)
  • GDELT global news: headlines on community, society, social progress
  • Twitter/X API: 50 recent English tweets on social wellbeing (non-retweets)
  • Reddit: Community discourse on social issues, public mood, civic life
  • Keyword sentiment analysis (positive/negative word ratio) with optional LLM

Data Sources (Live)

Hedonometer GDELT Twitter/X Reddit
🌍
03 — Environmental Care (15%)

What It Measures

Environmental progress: air quality, carbon intensity, biodiversity (including pollinator health 🐝), deforestation, and conservation sentiment.

Data Pipeline

  • Open-Meteo: Real-time air quality index (PM2.5, PM10, ozone) across global cities
  • UK Carbon Intensity API: Grid carbon intensity and fossil fuel mix
  • GDELT global news: headlines on environment, climate, conservation, pollution
  • GBIF: Wild bee occurrence records (Apoidea superfamily) — biodiversity proxy 🐝
  • iNaturalist: Citizen-science bee observations and species diversity 🐝
  • FAOSTAT: Global managed beehive population numbers 🐝
  • Global Forest Watch: Deforestation alerts and tree cover loss data
  • AQICN: World Air Quality Index — real-time PM2.5 from 5+ major cities
  • SerpAPI: Google search results for environmental progress and conservation

Data Sources (Live)

Open-Meteo AQ UK Carbon GDELT GBIF Bees 🐝 iNaturalist 🐝 FAOSTAT Global Forest Watch AQICN SerpAPI
❤️‍🩹
04 — Community Wellness (15%)

What It Measures

Public health outcomes, disease burden, life expectancy, maternal health, and community wellbeing indicators.

Data Pipeline

  • Disease.sh: Real-time global COVID-19 and infectious disease statistics
  • World Bank: Development indicators — poverty rates, education access, healthcare spending
  • WHO Global Health Observatory: Life expectancy at birth (WHOSIS_000001) via OData API
  • UN SDG Indicators: Maternal mortality ratio (SDG 3.1.1) and other sustainable development goals
  • GDELT global news: headlines on health, education, wellness, community outcomes
  • Reddit: Community discourse on public health, education, and civic life

Data Sources (Live)

Disease.sh World Bank WHO GHO UN SDG GDELT Reddit
💗
05 — Good Spend (15%)

What It Measures

On-chain activity: LefCoin transfers to verified good destinations in the GoodSpend Registry.

How It Works

  • Fully automatic — no oracle reporter needed
  • When LEF is sent to a registered charity/good destination, the LefCoin contract calls updateGoodSpend()
  • Score rises with cumulative good spend volume
  • Destinations are verified through LoveGovernance community voting

Verification

On-Chain Automatic Trustless
03

VERIFY IT YOURSELF

🔍

Read The Contracts

All smart contracts are deployed on Base Sepolia and readable on BaseScan. The LOVE Index calculation is entirely on-chain and deterministic.

Read Oracle Contract ↗
📡

Call getLoveIndex()

Anyone can call getLoveIndex() on the oracle contract directly. No API key needed. No middleman. Just Ethereum.

Query On-Chain ↗
💻

Run The Pipeline

The oracle pipeline pulls from 18 open data sources — most require zero API keys. Clone the repo and run it yourself to verify our sentiment analysis.

View Source Code ↗
04

WHAT WE DON'T CLAIM

Radical Transparency

We believe the biggest risk in "positive impact" crypto is love-washing — making vague claims about doing good without the infrastructure to back them up. Here's what we want to be clear about:

We publish everything: source code, contract addresses, methodology, data sources, and known limitations. If you find something we've missed, open an issue.