Basic Math Question I think... I apologize for the title.  I am not even sure how to phrase this question per se.  I feel like this should be easy and yet I am questioning my thinking.  Here's the scenario:
I have two groups.  Group A has 50 members.  Group B has 400 members.  What I want to know is what the calculation would be to adjust Group A to have the same "influence" on its other metrics (as if it also had 400 members).  So, if Group A had 50 followers and, for their last 1,000 tweets has a mean of 5 likes, what would be the number that I would use to multiply against the mean of 5 likes?
Example:
Group A: 50 followers, mean of 5 likes, total tweets 1,000
Group B  400 followers, mean of 20 likes, total tweets 1,000
Since Group B has 8X the number of followers, it would be obvious that they will have more likes (as they are reaching more people).  Is it as simple to say that Group A's 5 likes would need to be multiplied by 8 to adjust Group A to be the same as Group B?
Thanks for your assistance!

Comment continued with results from test procedures in R:
prop.test(c(5,20),c(50,400), cor=F)

        2-sample test for equality of proportions 
        without continuity correction

data:  c(5, 20) out of c(50, 400)
X-squared = 2.1176, df = 1, p-value = 0.1456
alternative hypothesis: two.sided
95 percent confidence interval:
 -0.03585336  0.13585336
 sample estimates:
    prop 1 prop 2 
  0.10   0.05 

Warning message:
In prop.test(c(5, 20), c(50, 400), cor = F) :
  Chi-squared approximation may be incorrect

Notice the warning message, triggered by the small counts in the first group. Because the P-value is so far above 5%, rejecting $H_0$ seems out of reach. But we don't need to
speculate because Fisher's exact test gives
a reliable P-value that is even larger.
fisher.test(TBL)$p.val
[1] 0.1931484

