Reference
Definitions for key terms used in Web3 analytics, InfoFi trading, and the Databot platform - KOL, alpha, InfoFi, discovery score, social signal, conviction, narrative, calls, on-chain signal, and revenue sharing.
Key terms used across the Databot platform, InfoFi trading workflows, and Web3 analytics. Each definition links to the relevant platform feature where it applies.
The layer of crypto where information flow, attention, and interpretation create trading edge independently of on-chain capital movement. In InfoFi workflows, the edge comes from seeing which accounts are leaning into a thesis and how fast that conviction is spreading before the signal reaches broad market consensus.
An influential figure in crypto whose commentary, calls, and portfolio activity are monitored as signal by other traders. KOL value as a signal source depends on track record and consistency, not just follower count. Databot monitors 500+ KOLs and surfaces when their activity clusters around the same token or narrative.
Non-public or early-stage information that gives a trader an edge before it becomes consensus knowledge. In practice, alpha often exists in the window between when a conviction signal forms in a monitored KOL network and when it reaches the wider market. The edge closes as more participants see the same signal.
A proprietary Databot metric that ranks emerging projects based on the intensity and breadth of KOL social activity, engagement velocity, and supporting on-chain signals. Higher discovery scores indicate more concentrated, sustained attention from monitored accounts, not just raw mention volume.
The degree to which a KOL's activity around a thesis appears genuine rather than performative, measured by consistency, clustering, and whether supporting context like on-chain flows and wallet activity aligns with the social behavior. Conviction differs from attention: attention can be manufactured, genuine conviction is harder to fake at scale.
A market-wide thesis that organizes capital and attention around a category of assets for a period of time. Narratives form in the KOL social layer before they move on-chain in size. Tracking narrative formation is a core use case for InfoFi tools.
When a KOL mentions a specific ticker on social media, this is referred to as a call, a signal that the account is publicly endorsing or drawing attention to that token. The Databot Calls dashboard tracks every ticker mention by monitored KOLs on X, giving traders a structured log of who called what and when.
A Databot signal that appears when multiple tracked KOLs mention the same token within a relevant time window. The key idea is overlap: consensus is stronger than a single call because several monitored accounts are pointing toward the same ticker at roughly the same time.
Databot's model of distributing a percentage of platform revenue to DATA token holders in qualifying tiers. The system is not yet active. Currently, revenue funds token buybacks and burns until a sufficient revenue level is reached.
Data derived directly from blockchain transactions that provides context for social conviction, including wallet flows, token accumulation patterns, liquidity depth changes, and exchange inflow or outflow. On-chain signals are used to validate or challenge social conviction signals. When both point the same direction, the combined signal is substantially stronger than either alone.
The moment several independent Databot surfaces point toward the same token, narrative, or project at once. A confluence setup can combine calls, KOL consensus, fresh discoveries, mindshare shifts, sentiment, or on-chain context, making it more actionable than any single isolated signal.
The process by which attention moves from one chain, sector, or theme to another. In Databot, narrative rotation is tracked by comparing changes in mindshare with market movement, which helps distinguish early KOL-led shifts from narratives that price has already recognized.
A burst of unusual smart-contract or token activity on-chain, often measured through elevated transaction counts, gas usage, or verified contract activity. Databot uses onchain surge as a context layer to see whether social attention is being confirmed by real network behavior.
A prioritized queue of noteworthy setups gathered from multiple Databot sources. Instead of forcing users to manually scan every dashboard, the Signal Inbox packages fresh discoveries, consensus, calls, and related context into a review list ordered by likely importance.
A saved set of tokens, projects, or discoveries that a user wants to revisit quickly. In the Databot workflow, a watchlist is not just bookmarking for convenience; it is a way to maintain a focused monitored universe as conviction develops over time.
A workspace layer for saving and organizing the setups that deserve follow-up. The Investigation Board sits after discovery and before decision: it is where promising signals are collected, compared, updated, and either escalated into deeper research or discarded.
Social Signal
Any measurable pattern in how influential accounts discuss a token or narrative, used as an input to trading decisions. A strong social signal involves multiple independent accounts, a tight timeframe, and consistency with on-chain context. A weak signal is a single loud mention without corroborating activity.