
How to Model Viral Growth: The Hybrid Model - nikunjk
http://www.linkedin.com/today/post/article/20121002124206-18876785-how-to-model-viral-growth-the-hybrid-model
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bwood
I actually have a paper published on this subject [1], except we use models
that have a basis in epidemiology. That article is unfortunately behind a
paywall, but here's an unbranded copy of an early draft of the paper [2].

We base our work off of the classical SIR model [3], which we extend to
include the possibility of reinfection (since it's possible to become
reinfected with a meme after initially losing interest). The key features of
the SIR model is a rate of infection proportional to the social interaction
between infected and susceptible individuals, where infected individuals
gradually lose interest (or not, depending on how the parameters are set).

With appropriate values for parameters, our model can very closely fit the
characteristic curves from viral infections, particularly those with an
initial large spike followed by a gradual taper, as you can see from these
Google Trends data [4]. The model can also be used to predict future infection
levels (assuming no change in system dynamics).

[1]
[http://www.sciencedirect.com/science/article/pii/S0307904X11...](http://www.sciencedirect.com/science/article/pii/S0307904X11002824)

[2] <http://stash.synchroverge.com/files/viral_memetic_model.pdf>

[3]
[http://en.wikipedia.org/wiki/Compartmental_models_in_epidemi...](http://en.wikipedia.org/wiki/Compartmental_models_in_epidemiology#The_SIR_model)

[4]
[http://www.google.com/trends/explore#q=two%20girls%20one%20c...](http://www.google.com/trends/explore#q=two%20girls%20one%20cup)

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bduerst
This seems trivial since it's assumed the users are "immortal" - never leaving
the product.

Maybe I'm not the target audience for this article though.

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rahulvohra
I plan to build up to a relatively complex model that hopefully you'll find
useful or interesting.

Here's my intended sequence: for the next post, I'll model retention as a
simple loss rate. After that I'll model retention with a curve over time. And
after that I'll model the viral factor itself as a curve over time.

Is there something in particular you think it'd be interesting to cover?

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far33d
As someone with a lot of experience modeling growth, I think this teaching
approach is a good one.

I find that most teams start exactly where this article starts - modeling
total installs over time using constant virality. They then realize they care
more about active users, and do the same for retention, then realize that
retention and virality change over time, and do a cohort model.

Jumping to the end is likely to confuse people who haven't already organically
gone through this process. I was also a little underwhelmed at first read, so
some mention of the plan in future posts would help us know where you are
going.

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nachteilig
And here I was hoping for a tutorial on virology viral growth curves ;o(

