  In this paper we explore the linguistic components of toxic behavior by using
crowdsourced data from over 590 thousand cases of accused toxic players in a
popular match-based competition game, League of Legends. We perform a series of
linguistic analyses to gain a deeper understanding of the role communication
plays in the expression of toxic behavior. We characterize linguistic behavior
of toxic players and compare it with that of typical players in an online
competition game. We also find empirical support describing how a player
transitions from typical to toxic behavior. Our findings can be helpful to
automatically detect and warn players who may become toxic and thus insulate
potential victims from toxic playing in advance.
