Introduction to Sybil Score and MEDIA Score

How to grow business with on-chain user analysis and segmentation is important for Web3 project. We aim to build the Web3 marketing analytics tools on user segmentation to drive growth through better onboarding, engagement and retention.

Sybil detection and scoring is the critical first step to accurately identify unique real-world users and filter out fake accounts or bots. Our proprietary MEDIA score goes a step further to profile and segment valuable users based on their on-chain behavior and characteristics.

With sybil score and MEDIA score, you'll gain unparalleled insights into user behavior, enabling you to optimize your onboarding, engagement, and retention strategies.

Sybil Score

Sybil attacks describe the abuse of a digital network by creating many illegitimate virtual accounts or bots. Sybil attacks will hurt not only Web3 projects, but also communities.

In TrustScan, we leverages AI and knowledge graphs to prevent sybil attacks. TrustScan can evaluate sybil scores for EVM-compatible EOA addresses by analyzing the Asset Transfer Graphs (ATGs) and user on-chain behaviors.

TrustScan currently supports sybil scoring across Ethereum and major Layer 2 including zkSync, Arbitrum, BNB Chain and Optimism. Over the next months we will rapidly expand support to additional emerging rollup networks including Starkware, Linea, Base and Polygon zkEVM to cover the most important Web3 ecosystems.

MEDIA Score

TrustGo introduces the MEDIA Score, a groundbreaking Web3 Account Value Assessment.

The MEDIA Score analyzes a user's on-chain activity across five key dimensions: Monetary, Engagement, Diversity, Identity, and Age.

With the MEDIA Score, users gain an unparalleled assessment of their on-chain value and activities. Developers can precisely identify their most loyal and engaged users to provide tailored incentives and rewards.

Quantifying on-chain reputation and contribution, the MEDIA Score unlocks the next level of personalized growth, community engagement and recognition in Web3 for both users and applications.