First, it’s an artificial, experimental network of real humans. Second, the adoption rates in that study top out at 50-60%. The paper in the OP concerned itself with finding a seed set which will produce a 100% adoption.
For real human of course you need a more detailed model than the simple linear threadshold one which was amenable to optimization by their algorithm. With a more detailed model they probably wouldn’t have been able to reach 100% but wouldn’t have tried to (e.g. if there is a non-adaption term I’d have strived for 100% divided by the non-adaption rate or something). But that doesn’t mean that you can tipp tippable populations.
First, it’s an artificial, experimental network of real humans. Second, the adoption rates in that study top out at 50-60%. The paper in the OP concerned itself with finding a seed set which will produce a 100% adoption.
For real human of course you need a more detailed model than the simple linear threadshold one which was amenable to optimization by their algorithm. With a more detailed model they probably wouldn’t have been able to reach 100% but wouldn’t have tried to (e.g. if there is a non-adaption term I’d have strived for 100% divided by the non-adaption rate or something). But that doesn’t mean that you can tipp tippable populations.