I see where you included metrics as a starting point like how long an article takes to read. Maybe like a word count approach as a starting point.
Thinking about understanding the content of an article and seeing who's most likely to be referencing that content in their post is more of what I had in mind.
Using page rank as suggested by OP, would provide weird incentives like frequent comments, or higher volume, could rank a person higher than if they had occasional comments further down the thread. If OP is interested in the most influential commenters, people who write frequently and have a posse, then PR would be a good way to do it. What would happen to a helpful comment from a throwaway account?
If there's more of a ranking algorithm, identifying who is most likely to have actually read the article could be neat.
What happens on a slightly different task where domain experts have tried to create a set of topics, not all domain experts talk to each other, and so we instead need a way to merge existing topics? I continue to see benchmarks where human expertise significantly outperforms AI on common sense reasoning tasks (most recently https://arxiv.org/abs/2112.11446).
What about an approach using directed acyclic graphs and entities?
It's a good point. Terrorizing an urban population with $200 drones doesn't seem like an unrealistic scenario. How would a tool like the F-35 be used to combat this situation? I think it would be fairly useless.
This makes me think of Liars Poker. There may not be anything special about what the traders are doing. They could just be in the right place at the right time.
Security. The alternative might be to let them make those choices then arrest them later. Or hit them with a drone strike. The filtering approach seems more compassionate.
https://atd.readthedocs.io/en/latest/atdgen.html