I have simulated a dataset for clicks on YouTube videos that records each click using dummy data. In the dataset, I collect information such as
device type and
userAgent. This dataset has no target variable such as
isFraud being 0 or 1, but I would like to implement it.
So, if this database recorded real world data, how would I be able to spot fraudulent activity / fraudulent patterns where people or bots are clicking on their videos in order to inflate the view count?
Should I check if repeating userAgents are clicking on the same videoURL every X minutes through the timestamp of the click? Maybe also check the screen width and height because there might be some weird values / nonexistent types there?
What data should I add to my dataset in order to create bot data, so the dataset can be used for predictive modeling?