How does one go about detecting large-scale inauthentic follower growth on Twitter? Generally, organized fake follower activity has two traits that set it apart from extremely rapid organic growth:Large fake follower networks follow the accounts they follow en masse (hundreds or thousands of fake followers from the same network in a short span of time).Fake follower networks tend to have anomalous creation date patterns, such as large batches of accounts created on the same day or within the same date range.Other patterns, such as having zero likes or zero tweets, weird follower/following ratios, large numbers of GAN-generated profile images, or repeated biographies often provide additional evidence that a group of followers is inauthentic. the website promoted by @markenetspanel1 offers Twitter followers for sales in quantities as large as 500,000Let’s take a look at an example account that has a high likelihood of having a large number of fake followers: @markenetspanel1, the “official” Twitter account of “social media management” site Markenet Panel (which sells Twitter followers, among other services). In order to analyze the followers, we first need to download them, which we can do with the Python library tweepy. To do this yourself, you’ll need to sign up for a Twitter developer account and get API keys if you haven’t done so already.# simple python script to retrieve a Twitter user’s followers # and save some useful metadata for each in CSV format # # this is intended as a simple example, and various optimizations # for efficiency and robustness…How to find swarms of fake Twitter followers