Signally references tweets with $crypto hashtags against a database of prices, giving us a ‘price_then’ for each tweet. Signally considers ‘a call’ the first time a user mentions a particular asset within a given time period and calculates a theoretical ROI based on that data point. From this signally can create many interesting analytics. You can click on the links in the table to explore the data further.
# | User | Calls | ROI | |
1 |
|
@Crypto_Dep | 237 | 5.9% |
2 |
|
@BagsyBot | 88 | 27.2% |
3 |
|
@BinanceUS | 7 | 42.2% |
4 |
|
@krakenfx | 22 | 11.6% |
5 |
|
@eliz883 | 71 | 6.8% |
6 |
|
@Chiliz | 13 | 50.0% |
7 |
|
@Bullrun_Gravano | 67 | 7.4% |
8 |
|
@CryptoCronkite | 6 | 20.7% |
9 |
|
@Blockchainsanta | 50 | 6.0% |
10 |
|
@luhosenpai | 8 | 26.8% |
11 |
|
@CryptoShadowOff | 6 | 50.5% |
12 |
|
@bitbitcrypto | 21 | 11.2% |
13 |
|
@CryptoMaestro | 10 | 16.1% |
14 |
|
@Hayess5178 | 31 | 9.3% |
15 |
|
@Degenertrade | 18 | 8.9% |
16 |
|
@cryptochimpanz | 17 | 12.2% |
17 |
|
@RampCapitalLLC | 2 | 42.0% |
18 |
|
@HackermanAce | 17 | 9.3% |
19 |
|
@TicTocTick | 28 | 5.9% |
20 |
|
@zorinaq | 1 | 78.7% |