How to Read the 29.5 Billion Yuan Fundraising Investment: After Changxin Technology's IPO, Technical Upgrades and Depreciation Must Be Calculated Together After Changxin Technology's IPO became a hot topic on the OKX planet, another official figure worth reading is the use of fundraising proceeds, rather than just focusing on the stock price. The prospectus shows that the total investment for three fundraising projects is about 34.5 billion yuan RMB, with planned use of raised funds at 29.5 billion yuan: 7.5 billion yuan for upgrading and transforming the memory wafer manufacturing mass production line technology, 13 billion yuan for DRAM memory technology upgrades, and 9 billion yuan for dynamic random-access memory (DRAM) advanced technology research and development. The funding direction is very clear, focusing on manufacturing, product generations, and forward-looking R&D. However, capital investment should not be judged solely by "scale." By the end of 2025, the company's fixed assets book value is expected to be about 183.024 billion yuan, accounting for 54.34% of total assets; fixed asset depreciation in 2025 is estimated at about 24.68 billion yuan. If the new production lines ramp up smoothly, they can increase capacity and reduce unit costs; if market prices fall, yield improvements fall short of expectations, or demand is insufficient, depreciation will still be included in costs. The prospectus also clearly lists risks such as fundraising project effects falling short of expectations, additional depreciation amortization, and DRAM cycle fluctuations. R&D intensity is also high. From 2023 to 2025, cumulative R&D investment is about 20.605 billion yuan, accounting for 21.67% of cumulative revenue during the same period; by the end of 2025, there will be 6,259 R&D personnel, accounting for 32.43% of total employees. This indicates the company is not simply expanding production but also advancing process and product generations. However, the return on R&D investment cannot be judged directly by the number of patents; ultimately, it depends on new product mass production, customer validation, yield, market share, and gross margin. Cash flow offers another perspective. In 2025, the company's net cash flow from operating activities is about 36.52 billion yuan, with revenue about 61.799 billion yuan, already demonstrating substantial core business cash flow; on the other hand, by the end of 2025, there remains about 36.65 billion yuan in accumulated unabsorbed losses. These two figures can coexist because DRAM manufacturing requires massive factories, equipment, depreciation, and R&D; cash flow, current profits, and accumulated losses are inherently different concepts. When judging fundraising investment effects, attention must also be paid to timing differences. Equipment procurement, installation, verification, and mass production will not be completed in the same quarter, and new capacity will not immediately translate into salable products. Early financial reports may first show construction in progress, fixed assets, and depreciation changes, with production volume, revenue, and cost improvements appearing later. Therefore, one cannot immediately convert the entire investment amount into profit just because fundraising is completed, nor can the progress of long-cycle projects be denied based solely on single-quarter net profit. Additionally, operating cash flow exceeding net profit is not uncommon; non-cash costs such as depreciation, changes in inventory, and receivables can cause differences. When comparing, operating cash flow, capital expenditures, and ending cash should be read separately, and checked for any one-time working capital changes. Only when several consecutive reporting periods show cash recovery and mass production efficiency improvements is it more appropriate to judge that fundraising investment is forming sustainable returns. Therefore, the post-IPO tracking table should at least retain six columns: actual fundraising investment progress, fixed assets and depreciation, R&D investment, DDR5/LPDDR5X product mix, gross margin, and operating cash flow. If assets increase simultaneously with improvements in yield, product mix, gross margin, and cash recovery, fundraising investment begins to convert into competitiveness; if only asset expansion occurs while market supply and demand weaken, risks will also increase. This article does not predict short-term prices but places the hot topic back into the investment and return framework verifiable by the official prospectus.

BTC community sentiment update: speed 1.60 times, current bearish sentiment clearly dominant Setting price aside, BTC community data itself has already shown two different clues. OKX Onchain OS recorded 73 mentions of BTC in one hour at 11:00 on August 2 (China time), including 69 on X and 4 in news; the total volume over 24 hours was 1094 mentions. Converted, the latest hour is 1.60 times the long-window hourly average, meaning about 60% higher than the 24-hour hourly average. This ratio only answers whether discussion is heating up, not whether buying pressure is increasing. Directly interpreting it as a breakout signal would be an unsupported inference. The tone structure is another clue. In one hour, bullish sentiment is 18%, bearish 52%, neutral about 30%, indicating "bearish sentiment clearly dominant"; over 24 hours, bullish is 26%, bearish 35%. The difference between short and long windows is the part worth tracking next. Regarding sources, BTC is currently mainly driven by X. When a piece of news is widely retweeted, mention volume quickly increases, but independent information may not increase proportionally. The trending list cannot tell us if each text comes from different participants, nor does it weight by account influence or capital scale. The long-window source can be treated as background: over 24 hours, BTC had 970 mentions on X and 124 in news. If the source ratio in one hour suddenly deviates significantly, it could be that new information first exploded on a certain channel, or simply that news updates have not caught up yet. Both explanations are reasonable, so we still need to wait for the original announcement or the next round of source distribution confirmation. I treat bullish and bearish as a thermometer on the same scale, not as precise votes. There is a lot of neutral content, usually just people watching without forming a consensus direction; increased bearishness may also mean more risk discussion, not that every poster has actually established short positions. The next step is to see whether spot trading volume expands, whether perpetual contract funding rates and open interest move in the same direction, and whether liquidations concentrate. These three data sets answer real trading participation and leverage structure, which cannot be replaced by community mention volume. If there are macro or industry events, the official original text should be checked directly. How to know if this time is wrong? If the next round of BTC mention speed returns near the mean and the gap between bullish and bearish narrows, this change was probably just short-window noise. Conversely, if speed increases for two consecutive rounds, news sources expand, and spot and derivatives trading also increase simultaneously, it is more likely that a market main trend is forming. Daily differences should also be retained. Community activity naturally differs between Asian early sessions, US trading hours, and around major announcements; a single 1.60 times figure is not suitable for annualization, nor should it be forcibly compared with raw counts from another platform. Continuous snapshots are more useful than a single nice number. So I record BTC as "discussion clearly accelerating, short-window tone with bearish sentiment clearly dominant." The official ranking stops here, with no proof that capital is betting in the same direction. If the next round improves source diversity and market trading together, it will not be too late to raise confidence in the judgment.

SOL currently shows a clear bullish dominance, but this is not yet the direction of capital flow. The popular numbers for SOL are easy to read; the difficult part is not mixing tone with capital direction. OKX Onchain OS recorded 27 mentions of SOL in one hour at 08:00 on August 2 (China time), with 27 mentions on X and 0 in the news; the total for 24 hours is 414 mentions. The latest hour is about 1.57 times the hourly average of the long window, which is approximately 57% higher than the 24-hour hourly average, classified as a "significant acceleration." This speed describes new discussions and does not necessarily correlate with price movements. The text tone is 63% bullish, 11% bearish, and about 26% neutral, currently categorized as "clearly bullish dominant." Over 24 hours, bullish is 55%, bearish 11%; if there is a discrepancy between the two windows, it should be understood as a change in discussion structure rather than a direct price target inference. I separate these two lines. A bullish tone with a slowing mention rate means the current discussion is positive but new attention is not accelerating; an increasing mention rate with bearish dominance may indicate risk or fault news attracting attention. Even if popularity and tone align, it cannot be directly equated to real buying pressure. Source is another limitation. Currently, SOL is "almost entirely driven by X." Community channels react fastest, and the same topic may be repeatedly reposted; the more concentrated the source, the more the next window needs to confirm. An increase in news mentions does not automatically mean the event is true; the original announcement remains the final verification standard. Within 24 hours, SOL mentions on X and news are 400 and 14 respectively; in one hour, 27 and 0. If the short window is more concentrated on X than the long window, sensitivity to reposts and single narratives should be heightened; if news proportion increases, check if it is just restating the same material. What really needs monitoring are SOL's on-chain transaction success rate, fees, active addresses, and major application usage, combined with spot trading, perpetual contract funding rates, and open interest. These data respectively answer usage demand and leverage participation; popularity rankings cannot replace them. Time lag also needs attention. The 414 mentions over 24 hours span different market sessions; dividing by 24 is just for comparison convenience and does not imply equal discussion volume each hour. Single deviations from the mean should be treated as observation points, not trend completions. How to judge if the recent activity was just noise? If the next round of mentions increases but tone quickly returns to neutral, the directional sense is likely caused by a small sample. If mention speed continues to rise and sources expand beyond a single community, attention can be considered gradually stabilizing. Ultimately, continuous data changes judgment, not a louder slogan. For now, remember three things: SOL discussion is clearly accelerating, the short window tone is clearly bullish dominant, and it is almost entirely driven by X. If speed continues and sources diversify, and trading and on-chain data also echo this, then push this observation one step further; until then, keep it on the watchlist and do not rush to act.

BTC, ETH, and SOL heat speed ratios are 1.51, 0.48, and 1.57 respectively: Who is really heating up? A common misunderstanding in the one-hour hot list is to directly treat total volume as a trend. The official snapshot from OKX Onchain OS at 08:00 on August 2 (China time) shows that BTC, ETH, and SOL were mentioned 69, 8, and 27 times respectively in the last hour; the 24-hour totals were 1094, 402, and 414 mentions. To compare the two windows, divide the 24-hour total by 24, then compare it with the latest one-hour count. The results are BTC 1.51 times, ETH 0.48 times, and SOL 1.57 times. A value above one means the latest hour is more active than the daily average; below one means relatively quiet. This only discusses speed, not returns. By this measure, BTC is clearly accelerating, ETH is clearly slowing down, and SOL is clearly accelerating. The asset with the highest raw mention count is not necessarily the one heating up fastest relative to its own baseline. Separating "highest volume" from "fastest acceleration" helps avoid many misjudgments. Tone also needs another layer of consideration. BTC is clearly more bearish, with bearish and bullish proportions at 42% and 10% respectively; ETH is slightly more bearish, at 38% and 25%; SOL is clearly more bullish, at 63% and 11%. The key here is the denominator. ETH has only 8 mentions in one hour, SOL 27, so a few new texts can significantly change percentages; BTC, although with a larger sample, may include retweets and quotes of the same event. When ranking by percentage, never forget how many texts are behind each group. The 24-hour average is not a perfect baseline either. It mixes different market sessions and smooths out spikes before and after announcements. A higher latest hour could be a new event or just an active period; lower could be natural cooling. Without continuous snapshots, a single speed can only describe the current position. A simple reverse check can also be done: if an asset’s mention speed exceeds double but bearish proportion also rises simultaneously, it should not be written as "heat turning bullish"; if bullish proportion is high but speed is only half the long-window average, it’s also inappropriate to say new consensus is expanding. Including these two counterexamples in the judgment framework helps avoid chasing conclusions based on a single attractive number. When I read such rankings, I consider three layers: look for turning points in one hour, see if it continues in four hours, and confirm if it becomes the main theme of the day in 24 hours. Finally, I bring back spot trading volume, funding rates, open interest, and on-chain activity to see if there is real market participation behind the attention. If the speed ranking of the three assets completely changes in the next round, this ranking is just a time slice; if the same asset leads continuously and the sentiment gap remains stable after sample size increases, then it’s worth raising tracking priority. Although this conditional judgment doesn’t have a catchy "must rise" phrase, it’s more convenient for verifying right or wrong later. Therefore, this dual-window data set is suitable for answering "where is heating up," but not for answering "where to go next" alone. Currently, the speed and tone of the three assets are not completely consistent; preserving this difference is closer to the data itself than compressing all numbers into a single bullish or bearish statement.

BTC was mentioned 69 times in one hour, is the sentiment aligned with the heat? Putting BTC's short-window numbers together with the full-day average gives a much more complete picture than just looking at the popularity ranking. OKX Onchain OS recorded 69 mentions of BTC in one hour at 08:00 on August 2 (China time), with 68 from X and 1 from news; the total for 24 hours was 1094 mentions. Converted, the latest hour is 1.51 times the long-window hourly average, meaning about 51% higher than the 24-hour hourly average. This ratio only answers whether discussion is heating up, not whether buying pressure is increasing. Writing it directly as a breakout signal would be an unsupported inference. Sentiment structure is another line. In one hour, bullish is 10%, bearish 42%, neutral about 48%, indicating "bearish clearly dominant"; for 24 hours, bullish is 26%, bearish 35%. The difference between short and long windows is what’s worth tracking next. Regarding sources, BTC is currently almost entirely driven by X. When a message is widely reposted, mentions increase quickly, but independent information may not increase proportionally. Popularity rankings don’t tell us if each text comes from different participants, nor do they weight by account influence or capital size. Long-window sources can be considered background: BTC had 970 mentions from X and 124 from news in 24 hours. If the source ratio in one hour suddenly deviates significantly, it could be a new message exploding on a certain channel or just news updates not yet caught up. Both explanations are reasonable, so we still need to wait for the original announcement or the next round of source distribution confirmation. I treat bullish and bearish as a thermometer on the same scale, not as precise votes. There is a lot of neutral content, usually just people watching without forming a consensus; increased bearishness may also mean more risk discussion, not that every poster has actually established short positions. Next, we need to see if spot trading volume expands, if perpetual contract funding rates and open interest move in the same direction, and if liquidations cluster. These three data sets answer real trading participation and leverage structure, which cannot be replaced by social mention volume. If there are macro or industry events, the official original text should be checked directly. How to know if this time we are wrong? If the next round of BTC mention speed returns near the mean and the bullish-bearish gap narrows, this change was probably just short-window noise. Conversely, if speed increases for two consecutive rounds, news sources expand, and spot and derivatives trading also increase simultaneously, it’s more likely the main market trend is forming. Daily differences must also be retained. Social activity naturally differs in early Asian hours, US trading sessions, and around major announcements; a single 1.51x multiplier is not suitable for annualization nor for hard comparison with raw counts from another platform. Continuous snapshots are more useful than a single nice number. So I record BTC as "discussion clearly accelerating, short-window sentiment clearly bearish dominant." The official ranking stops here, with no proof that capital is betting in the same direction. If the next round improves source diversity and market trading together, then increasing confidence in the judgment won’t be too late.

ETH Community Snapshot: Speed at 0.48x, Short Window Shows Slightly Bearish Bias ETH popularity should be viewed in two halves: one is how many people are talking, the other is the direction of the conversation. OKX Onchain OS recorded 8 mentions of ETH in one hour at 08:00 on August 2 (China time) in the official snapshot, including 7 on X and 1 in the news; totaling 402 mentions in 24 hours. The latest one-hour speed is 0.48 times the 24-hour hourly average, meaning it is about 52% lower than the 24-hour hourly average, indicating a "significant slowdown." This describes the attention rhythm but cannot replace price, volume, or capital flow data. In terms of sentiment, one hour shows 25% bullish, 38% bearish, and about 37% neutral, so currently "slightly bearish dominant." The 24-hour corresponding ratio is 36% bullish and 24% bearish; whether the short window is diverging from the long window is more meaningful than looking at one percentage alone. What concerns me most here is the denominator: only 8 mentions. A few more concentrated discussions could significantly rewrite the proportions; retweets, quotes, and news restatements might all be about the same event. Bullish or bearish can be reported as is, but should not be casually translated as how much capital has established positions in that direction. Currently, ETH's source structure is "mainly driven by X." If X mentions increase first and news remains low, it looks like the community is spreading first; if news also increases simultaneously, it only means more verifiable material is available, and details still need to be confirmed from original announcements by foundations, protocols, regulators, or exchanges. The 24-hour source background is 344 mentions on X and 58 in the news. Comparing this with the one-hour 7 and 1 mentions shows whether the new round of discussion has shifted communication channels. Channel changes themselves are neither bullish nor bearish but affect information speed and verifiability. For ETH, community signals are best cross-checked with two independent data lines. Network usage can be seen through fees, active addresses, L2 settlements, and staking changes; market structure through spot volume, futures basis, funding rates, and options skew. Any of these is closer to true demand than a single sentiment ratio. The 24-hour average also smooths out spikes caused by announcements and market sessions. If the latest hour is below the average, it may just be a quieter period; if above, it could be a single event intensifying. Only if two to three consecutive snapshots maintain the same direction does it look like a continuation rather than momentary noise. This set of ratios can easily be rewritten in the next snapshot. If the sample expands and bullish and bearish quickly return close, it means the previous movement was mainly driven by a small amount of text; if the sentiment gap remains and speed continuously rises, supported by on-chain usage or volume data, confidence can be adjusted upward. This round of ETH does not need to be forced into a big conclusion. Discussion has clearly slowed, sentiment is slightly bearish dominant, and the source is mainly driven by X. Remembering these three points is enough. It has not yet proven a breakout, net capital inflow, or on-chain demand change; whether this holds after the next sample expansion is the real focus.

SOL sentiment is slightly bullish but mention speed has not expanded: How to avoid overinterpreting popular rankings According to the official community sentiment ranking updated by OKX Onchain OS at 04:00 on August 2 (China time), SOL was mentioned 8 times in the last hour, with X accounting for 8 times and news 0 times; the total mentions in 24 hours were 474. Converted, the latest hour is about 0.41 times the long-window hourly average, indicating that the attention speed has not expanded in sync with the sentiment ratio alone. In the short window tone, the bullish proportion is 38%, bearish 13%, and neutral about 49%; in 24 hours, bullish is 50%, bearish 8%. The fact that bullish is significantly higher than bearish can be described truthfully, but it is still a classification of text samples, not a position vote, nor can it be used to infer a specific price target. This set of SOL data precisely illustrates that the two dimensions cannot be interchanged. A more positive sentiment direction answers the content tone; the mention speed of about 0.41 times answers whether the latest hour has accelerated relative to the daily average. If the direction is positive but discussion volume has not expanded, the reasonable conclusion is that the existing discussion is bullish, not that market consensus is rapidly increasing. The source of samples also needs to be retained. When there are 0 news mentions in one hour and X accounts for 8 mentions, the content may be mainly driven by real-time communities. Communities can reflect attention shifts fastest and are more easily influenced by repeated posts, slogans, and single events; therefore, the higher the source concentration, the more necessary it is to confirm continuity with the next time window. To convert SOL popularity into verifiable analysis, three data lines can be tracked. First is on-chain activity, such as transaction success rate, fees, active addresses, and major application usage; second is capital structure, such as spot trading, perpetual contract funding rates, and open interest; third is event sources, only using original announcements from foundations, protocols, exchanges, or regulatory agencies. None of these can be replaced by community rankings. The 24-hour comparison also has intraday bias. The 474 mentions include different market sessions; dividing directly by 24 is just a unified scale and does not mean the discussion volume should be exactly the same every hour. If mentions naturally rise in the next active US session, it cannot be immediately attributed to new events; news sources and sentiment ratios need to be observed simultaneously for changes. Recommended monitoring conditions are: mention speed is higher than the long-window average for two consecutive snapshots, bullish proportion remains stable after sample increase, and news or official sources no longer approach zero. If only one condition is met, the content tone should be maintained for observation; if bullish proportion is high but trading and on-chain activity do not correspond, especially the popularity should not be used as a reason to chase prices. As of this round, the accurate description of SOL is that the bullish text proportion is higher, the short-window discussion speed is about 0.41 times the 24-hour hourly average, and the source still leans toward X. This is closer to the data boundary than simply saying "the market is bullish on SOL." This article does not use unverified rumors nor generate images to reinforce sentiment; after the validity period ends, new snapshots will rebuild the content to avoid old ratios being scheduled after the market has shifted.

ETH's bullish sentiment exceeds bearish, but why can't short-term heat be directly regarded as a breakout signal? OKX Onchain OS's official community sentiment snapshot at 04:00 on August 2 (China time) recorded 12 mentions of ETH in the past hour, including 11 from X and 1 from news. There were 700 mentions in 24 hours; when converted to an hourly average over the long window, the latest hour's speed is about 0.41 times. This indicates that the current discussion pace relative to the long-term average is slower or faster, but it does not equate to price direction. Sentiment structure provides an additional layer of information beyond just total volume. In the one-hour ETH sample, bullish proportion is 25%, bearish 8%, and neutral about 67%; the 24-hour corresponding proportions are 40% bullish and 13% bearish. Bullish sentiment in the short window is clearly higher than bearish, but with only 12 samples, any concentrated event can cause rapid swings in proportions. These figures are best suited to answer "What is the current sentiment bias in ETH discussions?" rather than "How much capital is betting on a price increase?" Text classification does not read wallet positions nor weight each mention by capital scale. A highly interactive account and multiple small accounts are just text samples; retweets, quotes, and news restatements may describe the same event. Source breakdown helps judge the quality of the hotspot. If X mentions increase while news remains low, the topic may be spreading first within the community; if news sources rise simultaneously, it indicates more verifiable event material. However, an increase in news quantity does not guarantee positive content; one must return to original announcements from protocols, foundations, regulators, or companies to avoid filling in unconfirmed details with secondary headlines. For ETH, subsequent verification can be divided into two lines: network usage and market structure. Network usage includes fees, active addresses, L2 settlements, and staking changes; market structure includes spot trading, futures basis, funding rates, and options skew. Community bullishness only upgrades to a more reliable market judgment if partially corroborated by these independent data. Also note the limitation of the 24-hour average. Dividing 700 by 24 provides a convenient comparison baseline but smooths out spikes caused by releases, regulatory announcements, or US trading hours. If the latest hour is below the average, it may just be a time zone difference; if above, it could be a concentrated burst from a single news event. Observing two to three consecutive snapshots is required to discuss trend continuation. A more robust conditional statement is: if ETH's bullish proportion remains after sample expansion, mention speed rises again above the long-window average, and sources expand from solely X to multiple official or news channels, market attention can be considered more solid. Conversely, if the next round's total volume declines and proportions quickly return to neutral, the current result should be regarded as short-term noise. Currently, official data supports only two points: ETH's one-hour bullish sentiment exceeds bearish, and short-window discussion speed is about 0.41 times the 24-hour average. It does not prove a breakout, net capital inflow, or synchronous on-chain demand increase. The article sets a short validity period and retains original indicators to allow the next update to directly replace it, rather than letting attractive ratios become outdated conclusions without new evidence.

BTC heat is rising rapidly but bulls and bears are not aligned: Breaking down OKX one-hour and twenty-four-hour sentiment differences First, fix the observation window: OKX Onchain OS updated its official ranking at 04:00 on August 2 (China time), showing that BTC was mentioned 32 times in the last hour, including 28 times on X and 4 times in news. The total mentions in twenty-four hours were 1434, so the short-window mention speed is about 0.54 times the average hourly mentions over the whole day. This is attention speed, not trading volume or buying strength. Sentiment classification provides a second layer of information. In the one-hour sample, bullish sentiment was 34%, bearish 31%, and neutral about 35%; in twenty-four hours, bullish was 26%, bearish 31%, and neutral about 43%. When short-window heat rises, the bearish proportion still exceeds bullish, indicating that increased discussion and directional consensus are two different things. If you only look at the 32 mentions in one hour, the most common misjudgment is to directly translate "being talked about" as "someone is buying." The ranking aggregates text mentions, which may include risk warnings, macro commentary, product news, or repeated reposts. The majority of short-window mentions come from X, which spreads information quickly, and the same event may cause many similar expressions in a short time, so mention counts cannot estimate independent participants. Another misconception is treating bullish and bearish as precise votes. They come from text classification, suitable for comparing relative changes under the same source and method, but not for representing position ratios. When there is still a large amount of neutral content besides bullish and bearish, the market's real state may be increased attention but information not yet organized into a consistent trading direction. To determine whether BTC has shifted from a community hotspot to a verifiable market trend, the next step is to add at least three mutually exclusive data sets. First is spot trading volume and main trading session distribution to confirm if attention is accompanied by real transactions; second is perpetual contract funding rates, open interest, and liquidations to identify if leverage is overly concentrated; third is official macro or industry announcements to confirm if discussions have traceable event sources. Time comparisons should also maintain the same caliber. This round divides the twenty-four-hour total by twenty-four to get the hourly average, then compares it with the latest hour; this can only identify acceleration or cooling down and cannot eliminate intraday seasonality. Community activity differs across Asian, European, and US sessions, so a single 0.54 times should not be annualized nor directly compared with raw mention counts from another platform. More useful tracking conditions are: if the next round of BTC mention speed continues to exceed the twenty-four-hour average, and the proportion of news sources increases, and the gap between bullish and bearish narrows or reverses, then the discussion structure is changing. If mention volume quickly declines or only a single source repeatedly spreads, it should be regarded as a temporary attention spike. As of this snapshot, verifiable information for BTC is that attention ranks first, short-window speed rises above the long-window average, but bearish tone still exceeds bullish. This conclusion deliberately retains uncertainty because the official ranking does not provide price, capital flow, or account holdings. The article will expire within five and a half hours; subsequent content will only use updated official snapshots to prevent today's short-window numbers from occupying tomorrow's release queue.

Can one-hour heat represent a trend? Analyzing BTC, ETH, and SOL with dual-window data For the same popular ranking, changing the time window can lead to different conclusions. The official snapshot from OKX Onchain OS at 01:00 on August 2 (China time) shows that BTC, ETH, and SOL were mentioned 47, 15, and 17 times respectively in the last hour; the total mentions over 24 hours were 1434, 700, and 474 times. To avoid being misled by a single large number, the first step is to convert the two windows into comparable speeds, rather than simply dividing the one-hour total by the 24-hour total and claiming a market shift. The simplified method used here divides the 24-hour total by 24 to get the long-window hourly average, then divides the latest one-hour mention count by that. The results are approximately 0.79 for BTC, 0.51 for ETH, and 0.86 for SOL. A value above one means the latest hour is more active than the daily average; below one means relatively cooling down. This ratio only measures discussion speed and does not include price, trading volume, capital flow, or position information. After this comparison, BTC's attention speed is inconsistent with ETH and SOL. BTC is 26% more bullish and 32% more bearish in the last hour; ETH is 33% more bullish and 20% more bearish; SOL is 53% more bullish and 6% more bearish. Therefore, "mention acceleration" and "bullish sentiment" cannot be plotted on the same axis; the fastest heating asset does not necessarily have the highest bullish ratio. The 24-hour average is also not a perfect baseline. It mixes Asian, European, and American time zones and smooths out spikes before and after announcements. A latest one-hour below average may simply be entering a quieter period; above average may just be concentrated spread of a single event. Without continuous snapshots, a single speed measurement can only describe the current position and cannot prove a trend has been established. Sentiment ratios are also affected by sample size. ETH has only 15 mentions and SOL 17 in one hour; a small number of new texts can significantly change the percentage. BTC's larger sample size makes its ratio less likely to be altered by a single text, but it may still include retweets and repeated narratives. When comparing the three, one cannot rank solely by percentage without considering the denominator. A more complete validation should use at least three consecutive levels: identify turning points in the latest hour, judge continuation over four hours, and confirm if it has become the main theme over 24 hours. Only when mention speed continuously increases, sources are no longer concentrated in a few accounts or single news, and bullish and bearish structures remain stable as the sample expands, can "instant popularity" be upgraded to "sustained theme." Market data should be independently verified. Spot trading volume answers whether there is real trading participation; funding rates and open interest answer whether leverage is increasing; on-chain activity answers whether usage demand is changing. Community windows cannot replace these indicators; conversely, price increases do not prove all community discussions are positive. Separating different evidence into columns reduces bias from drawing conclusions before looking at data. Therefore, the purpose of this dual-window comparison is to rank "where heating is happening," not to predict "where it will go next." This article retains the original mention counts, sentiment ratios, and observation times for each window, setting a short validity period. After the next official snapshot appears, the system will recalculate with the new window, and the old article will no longer be scheduled, ensuring readers see verifiable market attention at that time, not numbers repackaged as the latest hours ago.

ETH's bullish sentiment is stronger than bearish, but why can't short-term heat be directly regarded as a breakout signal? OKX Onchain OS's official community sentiment snapshot at 22:00 on August 1 (China time) recorded 19 mentions of ETH in the past hour, including 15 from X and 4 from news sources. There were 700 mentions in total over 24 hours; when converted to an hourly average from the long window, the latest hour's speed is about 0.65 times. This indicates that the current discussion pace relative to the long-term average is either slower or faster, but it does not equate to price direction. Sentiment structure provides an additional layer of information beyond just total volume. In the one-hour ETH sample, the bullish proportion is 53%, bearish 21%, and neutral about 26%; the corresponding 24-hour proportions are 40% bullish and 13% bearish. Bullish sentiment in the short window is clearly higher than bearish, but with only 19 samples, any concentrated event can cause rapid swings in proportions. These numbers are best suited to answer "What is the current sentiment bias in ETH discussions?" rather than "How much capital is betting on a price increase?" Text classification does not read wallet positions nor weight each mention by capital scale. A highly interactive account and multiple small accounts are all just text samples; retweets, quotes, and news restatements may describe the same event. Source breakdown helps judge the quality of the hotspot. If mentions on X increase while news remains low, the topic may be spreading first within the community; if news sources rise simultaneously, it indicates more verifiable event material. However, an increase in news quantity does not guarantee positive content; one must still refer back to original protocol, foundation, regulatory, or company announcements to avoid filling in unconfirmed details with secondary headlines. For ETH, subsequent verification can be divided into two lines: network usage and market structure. Network usage includes fees, active addresses, L2 settlements, and staking changes; market structure includes spot trading, futures basis, funding rates, and options skew. Community bullishness only upgrades to a more reliable market judgment if partially corroborated by these independent data. Also note the limitation of the 24-hour average. Dividing 700 mentions by 24 provides a convenient comparison baseline but smooths out spikes caused by events like releases, regulatory announcements, or US trading hours. If the latest hour is below the average, it may just be a time zone difference; if above, it could be a concentrated burst from a single news item. Only by observing two to three consecutive snapshots can one qualify to discuss trend continuation. A more robust conditional statement is: if ETH's bullish proportion remains after sample expansion, mention speed rises above the long-window average again, and sources expand from just X to multiple official or news channels, then market attention is more solid. Conversely, if the next round's total volume drops and proportions quickly return to neutral, the current result should be regarded as short-term noise. Currently, official data supports only two points: ETH's one-hour bullish sentiment exceeds bearish, and short-window discussion speed is about 0.65 times the 24-hour average. It does not prove a breakout, net capital inflow, or synchronous on-chain demand increase. The article sets a short validity period and retains original indicators to allow the next update to directly replace it, rather than letting attractive proportions become outdated conclusions without new evidence.