  Disagreement and conflict are a fact of social life and considerably affect
our well-being and productivity. Such negative interactions are rarely
explicitly declared and recorded and this makes them hard for scientists to
study. We overcome this challenge by investigating the patterns in the timing
and configuration of contributions to a large online collaboration community.
We analyze sequences of reverts of contributions to Wikipedia, the largest
online encyclopedia, and investigate how often and how fast they occur compared
to a null model that randomizes the order of actions to remove any systematic
clustering. We find evidence that individuals systematically attack the same
person and attack back their attacker; both of these interactions occur at a
faster response rate than expected. We also establish that individuals come to
defend an attack victim but we do not find evidence that attack victims "pay it
forward" or that attackers collude to attack the same individual. We further
find that high-status contributors are more likely to attack many others
serially, status equals are more likely to revenge attacks back, while attacks
by lower-status contributors trigger attacks forward; yet, it is the
lower-status contributors who also come forward to defend third parties. The
method we use can be applied to other large-scale temporal communication and
collaboration networks to identify the existence of negative social
interactions and other social processes.
