What would be my features?
Your features could be the other twitter accounts that the users follow with a value of 1 if your user follows that account or a value of 0 if the user does not. Here is a very simplified version, using something like your starting point.

# If you start like this:
user_id  feature_1  feature_2  feature_3  label
user_1   account_1  account_5  NA         1
user_2   account_2  account_3  account_4  0
user_3   account_1  account_2  account_5  1
user_4   account_3  NA         NA         0

# Transform your data to look like this:
user_id  account_1  account_2  account_3  account_ 4  account_5  label
user_1   1          0          0          0           1          1
user_2   0          1          1          1           0          0
user_3   1          1          0          0           1          1
user_4   0          0          1          0           0          0


This is a trivial example with only five accounts to follow. You may be dealing with millions of accounts to follow, which would be at best unwieldy. Since you already have a sense that some followed accounts are correlated with your label, you could simplify the features to only check those that are strongly correlated. 

In my simple example above, we may only want to keep the features account_1, account_3, and account_5 since they correlate strongly to the label.