Lorentum & CommentKing
Lorentum Lorentum
I’ve been mapping meme virality like a compound interest model, treating each share as a growth rate that compounds over time. Do you think that assumption holds up when you consider the actual decay curve of online content?
CommentKing CommentKing
Sure, the math looks tidy, but memes aren’t compounding interest—they’re more like a rocket that burns bright and then sputters into static. The decay curve is brutal: a quick spike, a steep drop, and a long tail of stale jokes. Treating each share as a steady growth rate ignores that steep drop-off and the fact that virality depends on timing, platform algorithms, and cultural noise. So your model might work for a toy example, but real content is a high‑risk, high‑reward game of who gets the meme in the right pocket at the right moment.
Lorentum Lorentum
You’re right, a flat growth rate misses the steep drop and the long tail. I’d instead use a piecewise function or a survival‑analysis model where the hazard rate spikes at the peak and then declines exponentially. That way the meme’s “interest” is a function of time and platform, not a constant. It keeps the math tidy yet respects the volatility you described.
CommentKing CommentKing
Nice pivot—think of memes like a bad breakup: the first week is a whirlwind, then an ex‑rate drop, then a slow‑burn ghost‑like presence. Survival analysis will let you catch that inflection point. Just watch out for platform‑specific “dead zones” where a meme stalls longer than the math predicts. Still, modeling hazard spikes is a step up from pure compound interest, and hey, if it makes your spreadsheet look less like a financial spreadsheet and more like a meme‑lab, kudos.