

Bounding Viral Impact in Experiments - astuteajax
http://juneandrews.com/2015/02/27/bounding-viral-impact-in-experiments/

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astuteajax
Good Morning! I'm the author of the post and tried to highlight the salient
points. Please feel free to ask questions for a more indepth explanation of
application, derivation, etc!

I will be actively checking and answering questions today.

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Zephyr314
Great post. Quick question: Is there a way to artificially bound virality in
an experiment so that you don't need to partition the network without
destroying the signal?

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astuteajax
Ah! In some situations it is possible at the cost of a degraded user
experience.

Let's say we have an experiment that encourages sending likes. There are two
users here, the user sending the like and the user receiving the like. A
traditional a/b test flips a coin. If the coin turns up heads, then the user
receives the treatment. To control viral spread we want to flip a coin on the
interaction of the like. To implement with a traditional experiment framework
flip two coins, one for the user who could send the like and one for the user
who could receive the like. If both coins turn up heads, then the interaction
of the like receives the treatment.

A benefit is it allows us to test 2 hypothesis:

* Sending more likes is good for users

* Receiving more likes is good for users

However, the cost is an inconsistent user experience. If each coin is a 50-50
coin, then for a user sending the likes a random half of their network will be
featured. Similarly for the user receiving likes, they may not understand why
the sudden upturn in likes from some people when they may feel closer to
others in their network.

