Make Score Value to evaluate social popularity (from fb likes count)

Question

I have a list of websites and Facebook likes count for each of them. Count varies from 0 to millions.

For each website I want to make up some Score Value from 0 to 10, which would represent sites' social popularity.

Any thoughts how to deal with such a problem would be much appreciated.

Update:
Data summary:
Min. : 1
1st Qu.: 2
Median : 8
Mean : 908
3rd Qu.: 28
Max. :10841643

NebulousReveal · Accepted Answer · 2013-07-24 19:19:01Z

4

Maybe this would work: $$ \text{social popularity} = \frac{\text{count}}{\text{max count}} \cdot 10$$

answered Jul 24, 2013 at 19:19

NebulousReveal

4512 silver badges6 bronze badges

3

$\begingroup$ +1 I would suggest perhaps taking the log of the count (+1), because this kind of data will have an extreme right tail. Unless you do some kind of transform, you'll end up with the vast bulk of sites having a score of 0 or 1, and a handful with 9 or 10. $\endgroup$
– Hong Ooi
Commented Jul 24, 2013 at 19:27
$\begingroup$ It is indeed extremely right tailed. Min. : 1 1st Qu.: 2 Median : 8 Mean : 908 3rd Qu.: 28 Max. :10841643 Can you please write exact formula, where that log(count) should go. Thanks. $\endgroup$
– Viacheslav
Commented Jul 25, 2013 at 11:03
$\begingroup$ +1 for @HongOoi suggestion. Usually this type of web counters follows a Zipf curve, which, when is plotted as $x = log(rank+1)$ over $y = log(count+1)$ looks linear. Also, it depends on what you want to achieve with that score. $\endgroup$
– rapaio
Commented Jul 25, 2013 at 11:32
$\begingroup$ The skewness of the distribution is a fundamental feature of this kind of data, I disagree on using any log transformation. (+1) to snegostup's comment and (+1) to PEV's answer. $\endgroup$
– stochazesthai
Commented Apr 25, 2015 at 7:40

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