A most interesting thread popped up on Twitter Sunday from a data scientist who wishes to remain anonymous, regarding mail-in ballot data which strongly suggests fraud occurred in the wee hours of election night, when several swing states inexplicably stopped reporting vote counts while President Trump maintained a healthy lead over Joe Biden.
Using time series data ‘scraped’ from the New York Times website, the data – comparing several states (swing and non-swing) – clearly illustrates what fraud does and does not look like, and how several anomalies in swing states left ‘fingerprints of fraud’ as Biden pulled ahead of President Trump.
This is based on their proprietary “Edison” data source which would ordinarily be impossible to access for people outside the press. The CSV is available here (updated). And the script to generate it is here. I suggest that everyone back up both of these files, bc this is an extremely important data source, and we cant risk anyone taking it down.
What we are looking at will be time series analysis and you will see that it is extremely difficult to create convincing synthetic times series data. By looking at the times series logs of the ballot counting process for the entire country, we can very easily spot fraud.
One of the first things noticed while exploring the dataset is that there seems to be an obvious pattern in the ratio of new #Biden ballots to new #Trump ballots.
As we can see on this log-log plot, for many of the counting progress updates, we see an almost constant ratio of #Biden to #Trump. It’s such a regular pattern that we can actually fit a linear regression model to it with near-perfect accuracy, barring some outliers. How could this be possible? Is this a telltale sign of fraud? Surprisingly, as it will be shown, the answer is no! This is actually expected behavior. Also, we can use this weird pattern in the ballot counting to spot fraud!
Here is the same pattern for Florida. We see this linear pattern again.
And again (Texas)
And again (South Dakota)
And again all over the country. What appears to be happening is that points on the straight line are actually mail in votes. The reason they’re so homogeneous across with respect to the ratio of #Biden vs #Trump votes is that they get randomly shuffled in the mail like a deck of cards. Since the ballots are randomly mixed together during transport, spanning areas occupied by multiple voting demographics, we can expect the ratio of mail-in #Biden ballots to mail-in #Trump ballots will remain relatively constant over time and across different reporting updates.