The folks over at Northwestern's Knight Lab have a handy tool to occupy you until polls close tomorrow night: an app that predicts who your favorite people on Twitter are voting for. There is one caveat however: the machine can't figure out the Andrew Sullivans or Dave Weigels of this world. 

The actual app is called Tweetcast and more specifically, it uses an algorithm to predict whether a tweeter will sway Romney/Ryan or Obama/Biden tomorrow. "The system is most accurate — about 80 percent — with users who tweet about political issues. It’s less accurate — about 65 percent — with users who aren’t obviously political" its creator told the folks over at Northwestern's journalism school.  And who you mention on Twitter and how you mention also factors in:

Specifically the technology tracks words, @-mentions, hashtags and links in the Twitter feeds of known political supporters and compares those to the same elements in the feeds of other potential voters. The greater the similarity between the two, the more likely they are to support the same candidate, O’Banion said.

80 percent is pretty good (Nate Silver would agree!), but apparently Dave Weigel and Andrew Sullivan are no match for Tweetcast. Here's what happened when we put Weigel in, we got this: 

Fine, we know that he calls himself a libertarian and whatnot. But ... but .... look what happens when you put Andrew "talk me off the ledge" Sullivan into the machine:

Danger Will Robinson. Danger.  But you know, who knows, maybe the app is actually telling us the truth and Weigel/Sullivan will rip off their masks tomorrow and tell us they voted Romney/Ryan?  

And what about debate moderator Martha Raddatz, who conservatives thought was an Obama plant? 

 

And Salon's politico/ thorn in Donald Trump's side, Alex Pareene: 

And number wizard Nate Silver: 

Based on our initial observations, using the f-word, and words like "brown," "gay," and "equality" make the app think you will be voting blue. And @mentioning people like Lady Gaga, Rupaul, Lena Dunham, and Gabrielle Douglas make it think you will vote Obama too. Getting into twitter fights with Donald Trump, and mentioning Drudge Report will make the app think red. We also found that covering the campaign trail has an effect on your outcome:

 

The Atlantic's Politics Team

David Graham (@GrahamDavidA): Romney/Ryan

Conor Friedersdorf (@Conor64): Romney/Ryan

Garance Franke-Ruta (@thegarance): Romney/Ryan

Molly Ball (@mollyesque): Romney/Ryan

Buzzfeed's crew:

Zeke Miller (@ZekeJMiller): Romney/Ryan

McKay Coppins (@McKayCoppins): Romney/Ryan

Los Angeles Times

Maeve Reston (@maevereston): Romney/Ryan 

The New York Times

Jeremy Peters (@jwpetersnyt): Romney/Ryan

Michael Barbaro (@mikiebarb): Romney/Ryan

Ashley Parker (@AshleyRParker): Romney/Ryan 

And some others: 

Lindsay Lohan (@lindsaylohan): Obama/Biden. Lohan had announced her Romney endorsement last month.

Stacey Dash (@therealstaceydash): Romney/Ryan. Dash had announced her Romney endorsement last month.

Taylor Swift (@taylorswift13): Obama/Biden

Lady Gaga (@ladygaga): Obama/Biden

Bruce Springsteen (@springsteen): Obama/Biden

And the Most Important People of All: 

Gabriel Snyder (@gabrielsnyder): Obama/Biden because of the word "brown."

Jen Doll (@thisisjendoll): Obama/Biden because of her use of the "#gangnamstyle" hashtag. 

Richard Lawson (@rilaws) : Obama/Biden, also because of the word "brown." 

Elspeth Reeve (@elspethrb): Obama/Biden because she wrote "bullshit" and has an interaction with David Corn. 

John Hudson (@john_hudson): Romney/Ryan because of his use of the acronym "MSM"

Rebecca Greenfield (@rzgreenfield): Obama/Biden because she wrote "register" in a tweet a couple of times.

Alexander Abad-Santos (@alex_abads): Obama/Biden because he retweets Rupaul. 

Serena Dai (@ssdai): Obama/Biden she tweeted the word "equality."

Esther Zuckerman (@ezwrites): Obama/Biden she uses the f-word a lot. 

David Wagner (@david_r_wagner): Romney/Ryan because he uses the word "killed."

That all said, it's important to remember that these are predictions. And who knows what people will do in the voting booth? And while you spend some time thinking about that, just plug a few more names in.