My binary testing result shows that there exist a critical threshold on the frequency of automated postings in Twitter which demarcates user perception on a piece of information between spamming and insignificant useful information.
Applying the Law of Entrophy to this equation, we define each hour non-activity in terms of no tweet as a 0, and each hour of activity in terms of one tweet as a 1. Our objective is to determine the minimum amount of 0s to preced a 1, before that 1 can be perceived as a significant piece of useful information and thus not a spam.
The first configuration with the pattern 001 resulted in an average follower acquisition rate of +1/week. The current rate with the patter 00000000000000000000001 (23×0 + 1×1) resulted in an increase in average follower acquisition rate of +5/day.
I will leave this second pattern for the next two weeks before reducing a 0 from the pattern. Thereafter I will measure the average follower acquisition rate.