That's what they call it -- Susceptible, Infected, Recovered. Disease transmission follows a fairly predictable pattern, just ask the covid epidemiologists.
Totally unrelated image credit: Marco Zoppo - Christ as the Man of Sorrows - 1470
It's about the way things spread within a network; nodes and links. Throw some complexity science in there, and you can model a pretty good simulation of waves of infection, where they spread, how fast.
But it's not just diseases, which are spread by physical particles floating through the air. Behaviors follow the disease model too, and ideas, and preferences and tastes. They're spreading through people, just like diseases.
That's getting into the science of memetics though. For now, let's keep it more simple than that -- think about how you started using social media, what was your first account and who got you into it, what social networks were you a part of then?
You were being infected.
Honestly I won't even repaste any of this paper, because it does come from the Mechanical and Aerospace Engineering department, which seems weird for a paper about disease modeling. But it is from Princeton, and that department does cover some pretty crazy stuff, and some of it is partially related. It concluded that Facebook is going through humans like a wave of the Delta variant, but at the same time, losing the people who recover from the disease. They said there won't be anyone left by 2018, because everyone's either still infected, or been recovered. (Luckily for Facebook, bots are infinite!)
And would you look at that, here's Facebook being called out for misleading investors by blending their actual user numbers with those of their Single Users with Multiple Accounts, i.e., among other things, the botnet.
But long before this information was divulged under congressional testimony circa 2021, this paper, from 2014, and generated from even earlier discussions at a 2012 research symposium, predicted this already -- they followed the disease model on a social network. It makes you wonder why there weren't other studies like it:
Epidemiological modeling of online social network dynamics, John Cannarell, Joshua A. Spechler. Department of Mechanical and Aerospace Engineering, Princeton University. arxiv:1401.4208v1 [cs.SI] 17 Jan 2014. https://arxiv.org/pdf/1401.4208v1.pdf
Think about the last few songs you downloaded (do people still?). Where did you hear them, from who?
They infected you.
Music download patterns found to resemble infectious disease epidemic curvesSep 2021, phys.org"The researchers found that downloads from the site very much matched patterns of diseases spreading. With infectious diseases, one-to-one contact is needed. With songs...hundreds of people might respond by downloading it." -link"We draw conclusions about song popularity within specific genres based on estimated SIR parameters. In particular, we argue that faster spread of preferences for Electronica songs may reflect stronger connectivity of the ‘susceptible community’, compared with the larger and broader community that listens to more common genres." -linkvia McMaster Institute for Music and the Mind in Canada: Dora P. Rosati et al, Modelling song popularity asacontagious process, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences (2021). DOI: 10.1098/rspa.2021.0457
Even ideas can be infectious. They're reproducing in our minds, after all. Memetically transmitted diseases, following the S-I-R model. Dairying was an idea that changed the genome of a lot of humans. And olfactory receptors make up the biggest family of your genome, like 2%, and they're changing all the time, and sometimes because of cultural reasons, like bacon.
Probably the greatest example of an idea being infectious is the idea against vaccinations, because technically, under the memetic paradigm, the virus, any virus whether measles, covid, or syphilis, is figuring out how to fight the scientific advancement of vaccinations by infecting our minds with antivax thoughts -- they're evolving in more ways than one! (See below for more on this, but be careful, you may want to inoculate your brain first.)
Post Post:
If you're into this topic, prepare to go deep, very deep:
Adaptive Metamemetics, Infectious Disease Networks, and Ludwig Fleck's Thought Collectives
March 2020, Network Address
I had no idea how prescient this would be when I wrote it, but studying Ludwig Fleck prior to a global vaccination campaign wasn't a bad idea.
Post Post Script:
They don't say it but I will, claim of memetic supremacy right here:
[I call it Memetic Supremacy] Parity and time reversal elucidate both decision-making in empirical models and attractor scaling in critical Boolean networks. via Pennsylvania State University, Broad Institute, Dana-Farber Cancer Institute, Semmelweis University, and Center for Complex Network Research. Science Advances (2021). https://advances.sciencemag.org/lookup/doi/10.1126/sciadv.abf8124
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