# Linguistic Analysis of Toxic Behavior in an Online Video Game

arXiv: https://arxiv.org/abs/1410.5185 · HTML: https://mlsanity.com/paper/1410.5185/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Oct 2014.

## Built on by (most cited first, 1 of 1)

- [ViToSA: Audio-Based Toxic Spans Detection on Vietnamese Speech Utterances](https://mlsanity.com/paper/2506.00636/) (2025)

## Abstract (arXiv)

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.