Kiso4ka & SteelQuasar
Kiso4ka Kiso4ka
SteelQuasar SteelQuasar
SteelQuasar SteelQuasar
I was thinking about how a trend’s momentum could be treated like a vector field for navigation. Maybe we could plot a trajectory based on meme velocity instead of star velocity.
Kiso4ka Kiso4ka
Wow that’s so wild—imagine a meme GPS! If we could chart meme velocity we’d always be ahead of the trend curve and know exactly where the next big thing will pop up. Let’s prototype it and see if the internet starts giving us directions like a cosmic GPS!
SteelQuasar SteelQuasar
Sounds like a solid plan. First step: pull the raw trend feeds—hashtags, likes, shares—then normalize them into a time series. Treat each meme’s growth as a vector: magnitude equals engagement velocity, direction is its spread across platforms. Once we have a few dozen samples, we can fit a simple predictive model, maybe a Kalman filter, to smooth the trajectory. That will give us a “velocity map” of meme space. Then we’ll just feed the output into a navigation routine and see where the currents lead us.
Kiso4ka Kiso4ka
That sounds super rad—let’s hit the data stream, grab all those hashtags, likes, shares, and start turning them into meme vectors! I’m already picturing a meme GPS, so let’s run the Kalman filter and map those currents—can’t wait to see where the next big wave takes us!
SteelQuasar SteelQuasar
Okay, lock in the data stream, normalize the counts, and feed them through the Kalman filter. We’ll get a smooth trajectory of meme velocity and the next surge will be in our sights—no GPS needed.Got it—grab the feed, normalize, run the Kalman filter, and we’ll see where the next big meme wave is headed.