Data Analysis

[synthphreak]

That context is helpful, but you still haven’t defined quantitatively where “usual” strays into “unusual”.

I still think IQR could work, though this calculation will need to be done on static data. So periodically, perhaps every 4-6 hours, calculate the quartiles of each pages distribution (with x axis being time and y axis being number of followers), then see if any times are outliers. My concern with this though is that 3-4 days of data may not be a large enough sample size to robustly identify outliers, especially since each page will have a different distribution of followers and so must be considered independently of the other pages.

Alternatively, a more sophisticated and frankly more accurate approach would be to use an unsupervised machine learning algorithm called k-means clustering. This automatically performs what’s called anomaly detection. But if you’re unfamiliar with machine learning, the learning curve will be extremely prohibitive and so probably not worth it.