Linguistic Analysis of Toxic Behavior in an Online Video Game

TL;DR

This study analyzes linguistic patterns of toxic behavior in League of Legends, revealing how communication correlates with toxicity and offering insights for early detection to prevent harm.

Contribution

It provides a large-scale linguistic analysis of toxic players, identifying markers and transition patterns from typical to toxic behavior in online gaming.

Findings

Linguistic features distinguish toxic from typical players.

Communication patterns predict transition to toxicity.

Empirical evidence supports early warning mechanisms.

Abstract

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.