As a developer working on the Viral Ad Network (our advertainment network), and viral video search engine viral sauce (and with a recent MSci in Maths – so excuse the equations), I’ve worked on a fair share of social media ranking algorithms, so I found this discovery of the algorithms behind some of the top social sites very interesting. These are well sourced, and very informative to anyone in the middle of a viral seeding campaign. Here is a perfect example:
Reddit:
let
t = (t1 – epoch)
(where t1 is the time the post was made)
let x be the number of up votes minus the number of down votes.
Then,
let y be:
- 1 if there are more up votes than down votes,
- -1 If there are more down voets than up votes,
- 0 if there are the same number.
Now Let
z = max({x,1})
And We Have
ranking = C log10(z) + yt1
Where C is a constant (C = 45000).
You can find more algorithms in this great article.
Tags: viral advertising
