Tutorial | How to Find KOL's Transaction Address? Includes a File of One Hundred KOL Addresses

Original Author: Zibu, Crypto KOL

Due to their influence, KOLs can have a certain impact on projects through their actions. Typically, a project's KOL would first buy in themselves, then share in the community, and finally post publicly on channels like Twitter. If we have the KOL's address, we can know immediately what they bought, when they added to their position, and when they took profits or stopped losses.

This article shares some methods for finding KOL addresses and how to use these addresses.

1. Using gmgn

gmgn is a comprehensive platform with features such as trading, data analysis, and monitoring, and its founder is Chicken Brother @haze0x.

On gmgn, users can link Twitter accounts with addresses, allowing us to find KOL addresses using this feature.

For example, if we want to know 0xsun's address, we can enter "0xsun" in the search bar, and at the bottom of the search results, 0xsun's address will appear, as shown below:

By clicking on the address in the search results, we can see detailed information about 0xsun's address, as shown. We can see his Twitter follower count, with a clickable link to Twitter; we can see his win rate; and we can see his 7-day P&L, with a 7-day profit of $2.3 million.

Therefore, when we want to know the address of a KOL, we can search on gmgn to see if they have linked their address. If they have, we can find it there.

2. Using chain.fm

chain.fm is an on-chain monitoring platform where users have uploaded many smart contract addresses, including those of many KOLs. The founder is @zen913.

Before the new year, chain.fm launched a search feature supporting keyword searches, allowing us to use this feature to find KOL addresses.

I have mentioned this method in my tweet https://x.com/0x_zibu/status/1882345639218118884. There are two methods to find KOL addresses using chain.fm:

1. Directly Search for a Specific KOL Name

Let's continue using 0xsun as an example. Enter "0xsun" in the input field, and you will see several addresses appear, as shown in the image below.

The first address in the search results is listed in 426 channels, indicating a high probability that it is 0xsun's address. You can also verify this address on gmgn to see if 0xsun has authenticated it.

2. Search Using the Keyword "KOL"

You can also enter the keyword "KOL" to search for all relevant information on chain.fm, as shown below.

When you enter "KOL," all relevant channels will be displayed. These channels contain curated KOL addresses, and you only need to verify their authenticity.

Under the wallet option, using the keyword "KOL" will also display addresses containing this information, as shown below.

The addresses found through chain.fm are based on uploads by channel owners and cannot be guaranteed to be 100% accurate. It is necessary to cross-validate through gmgn, Twitter, or other channels.

III. Twitter-Based Forensic Analysis

The above two methods are relatively simple and can be found with some time and effort. However, some KOLs do not publicly disclose their addresses. In such cases, other methods must be used to find them.

1. Specific Display of Transactions

Some KOLs will display transactions in their tweets, including specific transaction information such as transaction time, buy or sell, transaction amount, and the quantity of the coin. It is easy to find addresses for these types of transactions as they provide specific transaction details for filtering.

For filtering such transactions, it is recommended to use DEX Screener (https://dexscreener.com/). You can filter based on transaction time, transaction type (buy or sell), transaction amount, and coin quantity, as shown in the image.

DEX Screener is one of the tools I have used with the most comprehensive manual filtering features. Unlike other tools where filtering features are superficial, I doubt even the PM uses them.

However, the drawback of TokenView is that it cannot retrieve transactions that use aggregation routes, such as those on OKX. For these transactions, you will need to check OKX's website (https://www.okx.com/en/web3) for information.

2. Vague Information

Sometimes, Key Opinion Leaders (KOL) on Twitter may not directly share their trades but instead mention entering a certain coin at a specific market cap. In such cases, the information provided is limited. Relying solely on one tweet may only give you a rough idea, and you may need to combine multiple tweets to pinpoint the exact transaction.

For example, yesterday, Cycle Bull shared Burder's address details as shown in the image. How can we identify this address?

Let's first gather all the relevant information:

(1) The tweet was posted at 9:53 on 2.5

(2) Based on the tweet, Burder first bought $Ncat and $Noland, followed by a purchase of $Calicoin

(3) The image in the tweet provides rich information, as follows:

a. The holding of $Calicoin is 4M

b. The holding of $Noland is 37.6M

c. The holding of $Ncat is 30M, but it accounts for only 57% of the total holding

d. At the time of the screenshot, their holdings were only 2 minutes old

(4) The opening time for $Calicoin was 8:23 on 2.5

From the above information, we can deduce that Burder's transaction occurred between 8:23 and 9:53, with a holding duration of 2 minutes as seen in the image. Therefore, the latest possible transaction time is 9:51. If Burder mentioned being late in the tweet, the earliest transaction time would be sometime after the opening but without specific details, so we can only start filtering from 8:23.

With this information, here's what we can do:

a. Write a script to fetch transaction data

Retrieve all buy transactions for the three coins between 8:23 and 9:53, and identify the address that made simultaneous purchases of these three coins in this timeframe, matching the order and quantity according to the collected information above.

b. Query Using Dune (https://dune.com/)

Compared to writing your own script to fetch transaction data, data on Dune is readily available. At this point, you can use AI assistance to write a Dune query statement, filter out addresses, and then manually verify them.

Four, Analyze Address Transaction Style and Win Rate

Once you have identified the KOL's address, you need to conduct a detailed analysis of this address. Look at their transaction style to see if they prefer playing in the primary market or the secondary market, whether they prefer chasing highs or setting ambushes, how they approach take-profit and stop-loss, what their win rate is, and what their overall profit and loss situation is.

For address analysis, platforms such as GMGN and Debot are currently quite effective.

1. GMGN

GMGN has done a great job in data analysis, covering various indicators.

For example, looking at the address of 0xsun, we can see their profit and loss, win rate, and total profit and loss for 1 day, 7 days, and 30 days. In recent profits and losses, we can see the trading pairs for the last 30 days, sort by various indicators, and click on a specific coin to see detailed transaction records. As shown in the image

2. Debot

Debot has implemented the same functions as GMGN, but the algorithms used are somewhat different, resulting in some discrepancies in the displayed data. Data for the address 0xsun on Debot, as shown in the image, can be compared with GMGN.

As for whether GMGN or Debot is better, my suggestion is to use both together, cross-reference them, and guard against data omissions or errors from a single tool affecting the analysis.

Five, Monitoring

After identifying the KOL's addresses and conducting data analysis, we need to categorize each address with tags and then use tools to monitor these addresses. This way, when they have transactions, we can know immediately, ahead of social media and Twitter.

For monitoring, Debot is highly recommended. Debot is currently the most feature-rich and detailed monitoring product I have used, with strong AI signals and smooth transactions.

Debot's wallet monitoring is divided into two types: wallet behavior monitoring and wallet group behavior monitoring, as shown in the image

1. Wallet Behavior Monitoring

This monitoring is a common feature in all tools. However, in other tools, all addresses are pushed to a single Telegram group. The advantage of debot is that it can group addresses and then push notifications to different Telegram groups based on the grouping, as shown in the image.

This allows for the establishment of different Telegram groups for monitoring based on tagging, such as addresses from internal exchange users, external exchange users, or addresses of special interest. A tool that can classify monitoring information is a good tool. When I used abot for monitoring before, to achieve grouped notifications, I had to tag the addresses first, and then the Telegram group would receive the monitoring messages, which required additional development to distribute them based on the tags. Now, with debot, I no longer need to do additional development.

2. Wallet Group Behavior Monitoring

If we are monitoring a large number of addresses, we face an unavoidable issue: excessive notifications. When there are too many messages, it can overwhelm the human brain and lead to information overload, defeating the purpose of monitoring. To address this issue, my previous strategy was to develop notifications further by setting criteria such as only sending notifications when a certain number of different addresses have made transactions within a specific time frame, for example, if 5 different addresses have made purchases within 30 minutes, then send a notification. I used this strategy for about a year, and it was very effective in reducing unnecessary messages while ensuring important updates were not missed.

debot's wallet group behavior monitoring perfectly implements the strategy I mentioned above, but in a more refined way with finer granularity, as shown in the image. We can monitor based on buying and selling, set monitoring time frames, transaction amounts, notification frequencies, and market cap sizes. This feature can fully meet various monitoring needs, and I highly recommend it.

VI. List of Top 100 KOL Addresses

Using the method mentioned above, I have compiled a list of nearly 100 KOL addresses, as shown in the image.

Everyone can analyze and tag each address based on the method described in the fourth section to identify addresses that align with their preferences for monitoring.

The file is uploaded on my Telegram channel and can be downloaded here: https://t.me/zibutalk/79

When sharing this file, please remember to give credit!

7. Summary

The above content introduced the method of finding KOL addresses, and also explained how to analyze and monitor addresses. For KOL addresses that are not included in the file, everyone can use the method above to find them. In addition, the address KOL presents publicly is just one of the addresses they use. Each person has multiple addresses, so you can find their associated addresses based on the above address and collect them to enrich your address database.

Each KOL has a different style, and some KOLs may even rug pull. Everyone should not blindly trust a KOL's address but should choose the one that suits them.

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