Last night, I began analyzing the Farcaster Pro data (basescan API + Neynar to retrieve user information using the wallet address). Found some interesting insights. I will write about a few, and attach the GitHub repos for anyone who wants to analyze them further. This is the data for the first 24h.

In addition to @mani's excellent analysis:
Almost 1,186 accounts has a FID of 1,090,000 or higher = brand new
These accounts got all no label, with is logical with a brand-new account. This is also the case for FIDs starting with 1,08#,###, but with less significant numbers (68) with no_label.

Overall in the first 10k:
- label 0: 2,036 (59.9%)
- label 2: 5,988 (20.4%)
- no label: 1,976 (19.8%)

You can find the data here:

working on aerospace applications during day time. building agents after sunset @rootnode | mani.ink

In addition to @mani's excellent analysis:
Almost 1,186 accounts has a FID of 1,090,000 or higher = brand new
These accounts got all no label, with is logical with a brand-new account. This is also the case for FIDs starting with 1,08#,###, but with less significant numbers (68) with no_label.

Overall in the first 10k:
- label 0: 2,036 (59.9%)
- label 2: 5,988 (20.4%)
- no label: 1,976 (19.8%)

You can find the data here: https://dune.com/queries/5200345

Interests: crypto, economics, TA & blockchain related innovations | 🔗 https://linktr.ee/cryptonjal 🔗 https://dune.com/nhejyht

Some of them 109xxxx even paid with warps

hamst.art $hamster /hamster 
martinvr.eth 
deploy.degen.eth

Interesting. Leave as few traces as possible. Perhaps for resale of such an account. The first 10k FC pro is clearly not a signal of quality casters or even that they are OGs.

Farcaster

FIDs that paid with warps

583095
273111
937457
576
189255
20510
976360
560744
433546
1886
3115
869347
570919
832728
14359
275716
285410
385727
565658
589773
571109
559986
239965
1735
657370
1091011
372916
570999
226939
347
22116
8847
4324
2433
539
707409
378
291566
241066
900723
784
415482
5818
317575
681790
5034
238260
909254
452663
191
1598
4698
550782
689495
18703
240339
4998
7774
429273
262813
237845
462542
762
607927
286046
1091430
227332
237985
7057
1091353
1091695
1091810
1091613
1091836
1091778
1091845
1091909
1091912
1091929
1091924
1091946
1091933
1091975
1091985
1092009
1092032
1092072
1092052
1092117
1092070
1092115
1092075
12142
1092188
345284
20771
1092261
1091809
599456
108
261364
1092390
18069
535436
264962
1092455
1171

I stored them here

https://farcaster.xyz/mvr/0x1f2d353f

Nice.
Just discovered this one https://farcaster.xyz/ajsjj09 42 followers, but all with a spam label 0.
Kind of amusing.

Not in the mood to copy and paste the Dune data to make a CSV-file, but at this moment it's easy to separate OG's from farming behaviour accounts.

Already done that. I need this data https://dune.com/queries/5200345
(mainly follower count  and spam_label).

Haha nice one. You can export dwr's Google doc as csv or you need more info?

dacht dat je je vakantie aan het boeken was

georgeorgeogegeege30 with a FID starting with 109, and the rest below the 1M. Nothing in between. Added it to my dataset.

I added pro accounts to my Farcaster Following Audit dashboard. I think that I'm going to distinguish them in
- Pro, 10k 🟩 = 1st 10k if FID is below 1089899 & spam label = 2
- Pro, 10k 🟥 = 1st 10k (farmer) if FID is above 1089899
- Pro, 10k 🟧 = 1st 10k rest of the first 10k
- Pro = subscribers who were after the 1st 10k