Steem Reputation, to Which Percentile Do You Belong?

Some days ago Hive account@cryptoriddler released a diagram render of how the reputation ranks are spread among all Steem accounts.

At the time of publication there were more than 530,000 Steem accounts (according to steempunks.com we are growing at an average of ~2,400 new accounts created/day in the last 30 days).

As noted by Hive account@cryptoriddler, more than 80% of all accounts have a reputation of 25, the starting reputation for each new account.

The image/render makes for some interesting reading.

• There are 16 different negative reputation levels on the platform right now, totaling less than 500 accounts
• Only 10 steem accounts have a negative reputation in the double digits (-10 or below)
• -18 is the lowest reputation on the platform right now (Hive account@berniesanders)
• 78 is the highest reputation (Hive account@steemsports)
• Less than 10 Steem accounts have a reputation higher than 75
• Only 17 Steemians have reputation 75 or higher
• The top 8 reputation levels have less than 50 accounts each
• Less than 200 accounts have reputation 70 or higher (196)
• The top 10 reputation levels (69-78) have less than 100 accounts each
• 64 is the highest reputation level with more than 200 members

• Only 30 reputation levels harbor more than 1,000 accounts each (26-55 - excluding reputation 25)

• No reputation level in the top 1% has more than 1,000 accounts

• Only 4 reputation levels have more than 5,000 accounts (26, 27, 28, 30 - excluding reputation 25)

• Only 1 reputation level is larger than 1% of the total accounts base (27 - excluding reputation 25)

• Only one reputation level below the starting level of reputation 25 has more than 500 accounts (17)

• Three reputation levels harbor more accounts than the directly lower reputation level (27, 53, 72)

• The 1% of Steemians by reputation starts in the higher bracket of reputation 56

• Less than 5,000 Steem accounts have a reputation above 56 (4,911)

All data referred to in this post comes from cryptoriddler’s render, who used Steem-Python to extract the data and visualized with Blendr.

Head over to cryptoriddler’s post to see the complete image and also a render of the situation around 3 months earlier.