Today is another enjoyable 8415 🤣

If Virtual Yapping is not tier scoring, I'll just eat it!

Basically, the number 8415 has maintained for many days now. If we calculate scores based on dynamic standards, my tweet data from the past few days must be randomly changing. Normally, the calculated score should also be random. According to my current understanding of the scoring calculation rules, the overall calculation rules for Virtual Yapping should belong to a comprehensive weighted scoring system, and this system is unrelated to the Kaito rankings. Some users not on the Kaito list still have high scores. For registered users, tier scoring is used, and scores are allocated based on the built-in system rankings. The allocation mechanism adopts a fixed quota system, where different rankings correspond to different scores. So it’s easier to understand why Yapping scores have always been 0; it's because the daily comprehensive ranking has not reached the “basis” for the system to distribute points. Currently, the lowest Yapping score I see is about the 250 tier; I previously thought it was a “registration system.” It still appears to be a ranking system, but the ranking is determined by a comprehensive coefficient. The significance of “persistence” lies not in being registered by the system but in improving the overall comprehensive ranking coefficient.

Yesterday's $VADER Yapping score was about 500 points, which is lower compared to before. According to the latest score allocation mechanism, the top 1000 users each day will receive VADER Yapping scores.

The current algorithm mechanism actually breaks down into three systems' Agent comprehensive scores.

1️⃣ Yaps scoring is determined according to Kaito's algorithm.

2️⃣ Arbus scoring is calculated according to the Arbus algorithm.

3️⃣ VADER Agent scoring is based on its own algorithm.

In terms of weight, the first two account for 70%. VADER Agent accounts for 30%. For new users, VADER has more advantages.

Actually, everyone feels it’s quite competitive; if the above assumptions are correct. Then for Virtual Yapping, the advantage of old users is actually “safety net.” Currently, if we calculate based on the overall score total, the earlier one outputs Virtual-related content, the more Yapping tier scores they can get, and if they output Virtual-related content later, unless the content quality is relatively high, the overall score increase speed is rapid and they have a place in the daily ranking, will they obtain corresponding scores. This assumption can also be proven through side factors, for example, a user who hasn’t output Virtual-related content for a period still can obtain Yapping scores, even seeing an increase in scores. This indicates that the current ranking system uses a certain time period as a calculation basis, where the ranking during that period determines the scoring factors.

VADER's scoring is because it’s a newly launched mechanism, so it has more advantages for new users. Actually, I basically update daily, so I wouldn’t say it’s particularly competitive. Some brothers who just started yapping actually output VADER more frequently than I do. Correspondingly, their VADER Yapping scores are also higher than mine, and currently, with the rising $VADER staking rate, more and more users are yapping. The ranking volatility is large, resulting in significant daily changes in the VADER Yapping scores. Next week should be a watershed; once the leaderboard appears, it will only get more competitive. Smart individuals should increase their output frequency these days to gain an early advantage in the rankings.

Back to the old topic of the weight issue between Chinese and English, actually, the yapping users in the Chinese area are indeed fewer compared to the English area. The initial assumption is that when the AI algorithm scores Agents, the language learning and recognition logic is based on English logic, and English grammar is easier for the system to learn. In the Chinese area, sometimes references and memes are preferred, which may seem like high-quality and in-depth articles to us, but AI algorithms may not necessarily understand them. There’s also the issue of high-frequency word stacking; if we look at individual tweets, an overabundance of homogenized content may lead the algorithm to “downgrade” the score. It seems we are always talking incessantly, but in the eyes of AI, it might just be too much nonsense. Ultimately, the quality of the article's content still relates to the so-called “interpersonal relationship governance.” Although it reduces the weight on likes, comments, and shares, taking Kaito as an example, the way ICT and ECT acquire scores is not the same, and the criteria for determining if an article has quality may differ for different users. But if AI itself has autonomous “evaluation” of articles, then what needs to be studied is how to make AI like it. 🤣