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Full List:
@BankOfBitcoin $100
@BitcoinCopper $100
@BitcoinDirect $100
@BitcoinFinance $100
@BitcoinIntl $100
@BitcoinNote $100 <-- Buy either, get both -- @BitcoinNote, @BitcoinNotes
@BitcoinNotes $100
@BitcoinPawn $100 <-- Buy either, get both -- @BitcoinPawn, @BitcoinPawnShop
@BitcoinPawnShop $100
@BitcoinPurse $100
@BitcoinTech $100
@BitcoinTreasury $100
@BTCCollector $100
@BTCNote $100 <-- Buy either, get both -- @BTCNote, @BTCNotes
@BTCNotes $100
@BitcoinSilver $500 <-- For a fork of @BitcoinGold, maybe using Scrypt?
@CryptoGold $500
@EarnBitcoin $400 <-- Buy this one, get all three @EarnBitcoin, @EarnBitcoins, @EarnBTC
@EarnBitcoins $250
@EarnBTC $250
@GPUMine $150
@GPUMiner $300 <-- Buy this one, get all three @GPUMine, @GPUMiner, @GPUMining
@GPUMining $100
@MineBitcoin $500 <- Buy this one, get both @MineBitcoin, @MiningBitcoin
@MiningBitcoin $150
@WinBitcoin $500
Feel free to make an offer on any of these.
Why this is valuable? ... if you have an account with a lot of followers but a crappy name (very common), you take one of these accounts with a great name (e.g., @EarnBitcoin) and move it aside (i.e., rename it), and then "move" your account that has existing followers to the name you just bought. And voila, ... you then have both a great name, and a great following.
Great names are nearly all taken already (since there is zero cost to register a Twitter account). These were mostly registered in the early years (i.e.., 2010, and 2011). So buying an existing name is a way to rebrand an existing account with a good name that will make it easier to grow going forward.
The value comes from the account name -- it is rare to find a decent Bitcoin-related Twitter account name that hasn't already been taken. For instance, if you have a faucet or something that pays out Bitcoin for some task, @EarnBitcoin is a great Twitter account name.
So the account is for sale, but the value is in the hard-to-get username.
Interested in an account but don't feel the asking price is right? Make an offer!
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That must be a record price (in BTC terms) for a [Edit: 1.0 BTC] Casascius, no? [Edit: And probably a record multiple against face value for any Casascius as well?] |
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There will likely be a fork with the Bitcoin Silver brand, someday. I am selling the @BitcoinSilver Twitter account. For $200 to the first to inquire. http://Twitter.com/@BitcoinSilver@BitcoinSilver Twitter account is for sale. bump |
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There will likely be a fork with the Bitcoin Silver brand, someday. I am selling the @BitcoinSilver Twitter account. For $200 to the first to inquire. http://Twitter.com/@BitcoinSilver@BitcoinSilver Twitter account for sale. bump |
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There will likely be a fork with the Bitcoin Silver brand, someday. I am selling the @BitcoinSilver Twitter account. For $200 to the first to inquire. http://Twitter.com/@BitcoinSilver |
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There will likely be a fork with the Bitcoin Silver brand, someday. I am selling the @BitcoinSilver Twitter account. For $200 to the first to inquire. http://Twitter.com/@BitcoinSilver |
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Are you still looking to buy?
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That link does not produce a download. Would you happen to be have a recent update? |
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I was curious how much revenue is coming from fees from the transactions which miners include in only the next one or two blocks., One problem with using OP's data (confirmation_times.csv) for this is that it uses a timestamp, instead of block #. So there's no real way to know how many confirmations it took for a transaction to get mined. But using the average of 1 block = 10 minutes, I should be able to get kind of close. What information this provides us is that miners receive ~%75 of their revenue from transactions they include within the first two blocks (well, within the first 20 minutes, to be technically accurate).  Generated using the following Python3 source for use in a Jupyter notebook. import pandas as pd
from plotly import graph_objs as go
from plotly.offline import iplot, init_notebook_mode
init_notebook_mode() # Jupyter notebook
data = []
daily_threshold = 10 # Ignore days w/less than N btc in fees.
filename = 'confirmation_times.csv'
col_names = ['conf_time', 'first_confirmed', 'fee', 'size']
labels = ['0+ minutes', '10+ minutes', '20+ minutes', '30+ minutes', '1+ hours']
bins = [0, 1*10*60, 2*10*60, 3*10*60, 6*10*60, 9999*10*60]
df = pd.read_csv('./{}'.format(filename), usecols=col_names, parse_dates=['first_confirmed'])
df['fee'] = df['fee'] / 100000000 # Use BTCs, not Satoshis.
df['date'] = pd.to_datetime(df['first_confirmed']).dt.date
df['time'] = pd.cut(df['conf_time'], bins, labels=labels)
grouped = df.groupby(['date', 'time'])
df2 = grouped['fee'].sum().to_frame().rename(columns = lambda x: x + '_sum')
s = df2.unstack()['fee_sum'].sum(1).ge(daily_threshold)
plot_df = df2.loc[s.index[s].tolist()]['fee_sum'].unstack()
for time_bin in list(plot_df):
data.append(
go.Bar(
x=['{:%Y-%m-%d}'.format(dt) for dt in list(plot_df[time_bin].index)],
y=plot_df[time_bin].tolist(),
name=time_bin))
layout = go.Layout(
barmode='stack', title='Bitcoin Mining Fee Revenue By Confirmation Speed',
xaxis=go.XAxis(title='Date', type='category'),
yaxis=go.YAxis(title='Total Fees (BTC)'))
fig=go.Figure(data=data, layout=layout)
iplot(fig, filename='stacked-bar') |
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For the first 20,000 blocks, the issuance is limited by the "slow start" algo. Each block the $ZEC issuance increases. At block 100, it was (100 / 20,000) * 12.5 $ZEC = 0.0625 $ZEC. With the target of 576 blocks/day, that means 36 $ZEC / day rate at block 100. Blocks are targeted to come at the rate of one every 2.5 minutes. (12.5 $ZEC every 2.5 minutes is the same as 50 $ZEC every 10 minutes, the same rat that Bitcoin started out with.) At the current block, ~660 it is (660 / 20,000) * 12.5 = 0.4125 $ZEC per block. With the target of 576 blocks/day, that means 237.6 $ZEC / day rate at block 660. At Polo price of 19 BTC/ZEC, that's issuance at the rate of about $3M USD per day. 20% of that to the founders, 80% to the miners. It's been just 8 hours since launch, and ZCash is already well into issuance of "day 2"'s coins. This slow start is slow, sure. But not anywhere near as slow as the "target" chart shows. Incidentally, at this moment, with 850,000 Sol/S ( https://explorer.zcha.in/ ) at this very moment in time, and have a $200 AMD 470 GPU ... you're getting ~20 Sol/S on it, worth about $70/day. |
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Sold, on OpenBazaar. Thank you!
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We would appreciate your perspective on this topic. With opt-in replace-by-fee, it becomes trivially easy to "cancel" a zeroconf transaction. |
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I've got family in Africa. You'd be pretty goddamn amazed where great coverage appears.
Not just wide coverage but cheap too! Want just a couple dozen MB of data service? Pay $0.25 for a scratch-off code and you got it! |
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[Edit: No longer for sale.]
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