researchers studied 40 million posts made by 1.7 million web users .
from this they divided people into two groups - future-banned users -lrb- fbus -rrb- and never-banned users -lrb- nbus -rrb- .
they built an algorithm that scans posts for signs of antisocial behaviour .
study shows this algorithm can identify potential trolls in 80 % of cases .