In the Web3 ecosystem, users are often trapped by the "disconnection between data and sentiment"—seeing a certain token's "small to medium wallet growth of 10%" but not knowing whether this reflects genuine community enthusiasm or blind following by retail investors; discovering a certain NFT's "transaction frequency has surged," unable to distinguish whether it is a consensus explosion or a volume manipulation. The "market sentiment" behind on-chain data is hidden in the details of capital behavior and address interactions; traditional tools only provide numbers without "emotional answers," leading to decisions that miss the core. Bubblemaps breaks out of the "data display" framework, centering on "sentiment translation," and innovatively creates the "on-chain sentiment index," transforming "capital flow, holding changes, and address interactions" into intuitive emotional labels of "panic, frenzy, calm, wait-and-see," allowing cold data to "speak its feelings," enabling users to see through the market's real state at a glance.
1. "Capital sentiment translation": Understanding the "attitude of money" from transfer behaviors
Capital is the "barometer" of market sentiment—large amounts of capital quietly flowing into exchanges may indicate a "calm profit-taking," while small to medium funds rushing into new mining pools may reflect "frenzied following." Bubblemaps' "capital sentiment translation module" analyzes the "transfer scale, frequency, and destination" of funds, labeling each capital movement with an emotional tag, and aggregating to generate a "capital sentiment heatmap."
For example, if a certain token has a "top address transferring 5,000 units to an exchange with no subsequent inflows," the module will label it as "calm exit sentiment"; if "over 200 small to medium wallets concentrate on transferring to a mining pool within an hour, and these wallets are mostly newly registered," it is judged as "blind frenzy sentiment." The heatmap uses red (frenzy), yellow (wait-and-see), blue (calm), and black (panic) to distinguish emotional intensity: a certain DeFi mining pool's capital sentiment heatmap shows "80% of the area is red," indicating current capital inflow is frenetic, and the module will prompt "beware of subsequent selling pressure"; a certain NFT series' capital heatmap shows "65% blue," indicating that old players hold positions calmly, suggesting "consensus is relatively stable, focus on long-term value." A user saw that a certain Meme coin's "capital sentiment heatmap is all red," judging it as short-term frenzy, decisively giving up on chasing highs, and three days later, the token indeed plummeted by 40%.
2. "Address sentiment translation": Understanding "people's intentions" from holding and interactions
The user behavior behind the address hides the truest emotions—old players increasing positions indicates "strong optimism," while new addresses registering in bulk but not trading may indicate "wait-and-see." Bubblemaps' "address sentiment translation engine" interprets the emotional tendencies of different types of addresses by analyzing their "holding duration, interaction frequency, and associated behaviors."
The engine classifies addresses into three categories and translates emotions:
• Old player address (holding for over 6 months): If "continuously increasing positions with no outflows," it translates to "long-term optimism sentiment"; if "starting to transfer out in small batches," it is labeled as "cautious profit-taking sentiment";
• New user address (registered for less than 30 days): If "buying and immediately staking to participate in the ecosystem," it translates to "active participation sentiment"; if "buying and remaining inactive for a long time," it is judged as "wait-and-see sentiment";
• Project-associated address: If "transferring to an ecological fund rather than an exchange," it translates to "ecological construction sentiment"; if "suddenly transferring to multiple hidden addresses," it suggests "potential risk sentiment." An NFT collector used the engine to discover that in the past 7 days, "80% of the addresses of old players had increased positions," determining that community sentiment was strong, and after acquiring, the series rose 2 times due to consensus.
3. "Market sentiment index": A "decision-making compass" aggregating emotional signals
The sentiment of a single capital or address is limited. Bubblemaps aggregates all emotional signals to generate the "on-chain market sentiment index," presenting the market state intuitively with a score from 0 to 100: 0-30 points for the "panic zone" (capital fleeing, addresses primarily waiting), 30-70 points for the "calm zone" (balance between bulls and bears, stable sentiment), 70-100 points for the "frenzy zone" (capital clustering, blind following).
The index will also label "core emotional driving factors": if the index suddenly rises to 85 points (frenzy zone), it will prompt "driving factor: after a certain KOL's recommendation, small to medium funds surge in, and old players show no significant increase in positions," suggesting that the sentiment may not be sustainable; if the index falls to 25 points (panic zone), it will mark "driving factor: a certain security incident triggered mass outflows from top addresses, need to pay attention to official responses." A certain institutional investor used the sentiment index to short a certain token when "the index rose to 90 points with the driving factor of 'retail following,'" and to buy when "the index fell to 20 points with the driving factor of 'miscommunication of bad news,'" doubling returns within six months.
Summary
From reading the attitude of money through "capital sentiment translation," to understanding people's intentions through "address sentiment translation," and finally to providing a global judgment with the "market sentiment index," Bubblemaps uses "sentiment translation" to give Web3 data a "temperature." It is no longer a "tool that only provides numbers," but a "translator" that can understand the mood of the market—helping users avoid the traps of "frenzied chasing of highs and panic selling," and seize opportunities for "calm layouts and rational profit-taking," making on-chain decisions truly align with the market's real sentiment and significantly improving decision-making success rates.
