  Online communities have gained considerable importance in recent years due to
the increasing number of people connected to the Internet. Moderating user
content in online communities is mainly performed manually, and reducing the
workload through automatic methods is of great financial interest for community
maintainers. Often, the industry uses basic approaches such as bad words
filtering and regular expression matching to assist the moderators. In this
article, we consider the task of automatically determining if a message is
abusive. This task is complex since messages are written in a non-standardized
way, including spelling errors, abbreviations, community-specific codes...
First, we evaluate the system that we propose using standard features of online
messages. Then, we evaluate the impact of the addition of pre-processing
strategies, as well as original specific features developed for the community
of an online in-browser strategy game. We finally propose to analyze the
usefulness of this wide range of features using feature selection. This work
can lead to two possible applications: 1) automatically flag potentially
abusive messages to draw the moderator's attention on a narrow subset of
messages ; and 2) fully automate the moderation process by deciding whether a
message is abusive without any human intervention.
