🚨NEW VIDEO🚨 💢Starfleet Academy is TRASH -- FINALE youtu.be/qFISoOiBUGA

you have to be too chronically online to be excited for this

everyone hates knickas

Why would you prove their point like this?

RT @joeybtoonz: These aren’t Knicks fans. These are cancer cells.

😆

The Adventures of Mighty Max G G #199

“I’m in my 50s and totally broke and it’s Elon Musk’s fault” Have some decorum

Its brave when a shaved transmonke takes a stance

This looks like a promo image for a family sitcom about a solo dad with his gay son, smart daughter, and evil son

This whole episode is gold.

DOWNGRADE.

"Brian Tyree Henry is rumored to be playing Harvey Dent." ...he lost 150lbs for the role, right?

When they mess up the circumcision.

Big announcement! I have created an algorithm which estimates the number of followers that individual accounts gain from their viral Twitter posts. Over the past year, I've been tracking many accounts with suspicious engagement metrics, and I'm finally able to use this data to highlight the suspicious vitality of accounts like @esjesjesj. I've tracked the hourly followers gained by these accounts over time in addition to the like counts of all of their Tweets, and by cross-referencing this data, I can estimate the proportion of followers gained from any individual tweet. Obviously this is not 100% accurate for many reasons, but it does provide a plausible guess as to how many followers can be attributed to each individual tweet. To be more specific, I created a model for the distribution of likes tweets gain over their lifespans, which factors in the virality of the tweet and the time of day the Tweet was sent in order to create a plausible representation of how many likes each tweet gained during each hour that it was active. I can cross-reference this data with all the other tweets which were active during the lifespan of any individual tweet in order to estimate the total follower growth that can be attributed to it. Obviously this system isn't perfect. It relies on estimates for engagement longevity. Measuring the actual hourly like counts would cost me tens of thousands of dollars a month, so that isn't an option. Another thing I'd like to do is measure the engagement of the reply sections to expose how suspiciously barren they are, but once again that would cost a lot of money in API usage. The results from this are fascinating. Firstly, as you might have expected, accounts like @esjesjesj exhibit unbelievably suspicious follower growth in proportion to the virality of the tweets. The only account I've tracked which exhibits more suspicious virality is @DreamLeaf5. The only other accounts which come remotely close to such a low score are ones which already have such a critical mass of followers that it makes sense for them to have a lower follower growth rate because so many of the people who would be interested in their content are already following them (such as @ShitpostGate). It would make sense for meme accounts in general to experience less follower growth than average, but they still greatly outperform accounts like @esjesjesj and @DreamLeaf5. However, accounts like @esjesjesj are the complete opposite of this. You would expect them to experience immense follower growth because they are a medium-sized account which constantly experiences viral tweets. In reality, if this engagement was authentic, his account would be experiencing more growth because the hundreds of thousands of people who like his tweets on a daily basis would actually start following him. For a specific example, @esjesjesj's most viral tweet with over 1 million likes resulted in an estimated follower growth of just 400 followers. Yes, you heard me correctly, one of the most viral tweets ever posted on this platform only netted him 400 new followers. So what am I going to do with this data? From now on, I am going to be focusing on posting content which I have measurable data to back up my claims on. There are limitations of this new system which prevents me from tracking tweets/accounts retroactively. Essentially, I need to be tracking an account ahead of time in order to calculate an estimate for how many followers were gained by a post. If you have any suggestions for accounts with suspicious metrics which I should watch, let me know and I will add them to my tracking system. Starting out, I will focus on posting the most egregious examples of posts with suspicious engagement from the handful of accounts I have been tracking. One final disclaimer that these are rough estimates using very limited data. Please share this post to support me and justify all the hard work and money that went in to create this!

2027 “Netflix presents” *cold open* *shot of bulky skinhead, late-40’s, covered in prison and neo-Nazi tattoos walking* Skinhead: You’re in my fucking spot, [hard R]. 5 year old black boy: I-I didn’t know, I-I was just studying, I’m so sorry… Austin. *title drop* “Innocence”

We kill and eat animals to survive, you killed your kid because you didn't want a gross disabled person in your presence Get fucked

You felt compelled to look for bible passages after putting meat in your mouth...I'm sure there's a message in there...

Fr?

Their fries are dogshit