  The moderation of content on online platforms is usually non-transparent. On
Wikipedia, however, this discussion is carried out publicly and the editors are
encouraged to use the content moderation policies as explanations for making
moderation decisions. Currently, only a few comments explicitly mention those
policies -- 20% of the English ones, but as few as 2% of the German and Turkish
comments. To aid in this process of understanding how content is moderated, we
construct a novel multilingual dataset of Wikipedia editor discussions along
with their reasoning in three languages. The dataset contains the stances of
the editors (keep, delete, merge, comment), along with the stated reason, and a
content moderation policy, for each edit decision. We demonstrate that stance
and corresponding reason (policy) can be predicted jointly with a high degree
of accuracy, adding transparency to the decision-making process. We release
both our joint prediction models and the multilingual content moderation
dataset for further research on automated transparent content moderation.
