Thread by @benimmo

Having studied IO for longer than I care to remember, one of the most frequent comments I’ve heard, and agreed with, is that we need better ways to assess impact on multiple levels and timescales.

As part of that, we need a way to assess live IO in real time.

This paper suggests a way to approximate impact in the moment, when we don’t have the full picture, including the IO operators’ strategic objectives, or the luxury of taking the time to run polls to measure effect on public sentiment (hard even in normal circumstances).

This field is rapidly developing, but we need to start somewhere. Without clear context and a comparative scale, there's a danger of IO capitalising on fear and confusion to claim an impact they never had.

Remember the midterms in 2018?

There’s more to this than can be said in a thread. If this paper contributes to the discussion, and helps IO investigators make the tough prioritisation calls when they’re needed, it’ll be a good start.

brookings.edu/wp-content/upl…

I’d love to hear ideas for measuring the cumulative effect of IO. Come to that, I’d love to see a peer-reviewed definition of what cumulative / strategic impact is.

There are tricky questions to this. What’s the unit of accumulation – operation, threat actor, country of origin? How do we weight for spam-posting vs complex IO? How do we define the target of the operation if we don’t know the operator’s intent?

What’s our baseline? Remember, we always end up studying IO after the fact. Where do we consider the start to be, and how do we retrospectively measure the situation then compared with the situation now?

This is going to be a long-term challenge, and we do need long-term ways to measure effect.

But with the most targeted election in years coming up, we also need a clear, fast way to put IO in context, so we can all keep our balance and respond where it’s needed most.