Similarly, when memes are born and bred, it would be useful to know whether one or another started at a site with a certain frog as an avatar. While this is technically complicated its far less complicated than the facial recognition that social platforms have today.
A Call for Cooperation Against Fake News
Jeff Jarvis
1K129

The University of Indiana has already done some excellent work in this area. Their Meme Diffusion Network videos visualize the growth of hashtags, making it easier to spot when a tag is being artificially trended through the actions of a botnet or a co-ordinated group of users.

They have a database going back to 2011. This gives you the opportunity to examine the evolution of influence strategies as well as identifying current practices.

Notice the burst of activity in this example from Summer 2015. Several of the most active accounts your see here were run by the same person.

https://www.youtube.com/watch?v=IYYoGJR2XSs

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