  In this dataset paper, we present a three-stage process to collect Reddit
comments that are removed comments by moderators of several subreddits, for
violating subreddit rules and guidelines. Other than the fact that these
comments were flagged by moderators for violating community norms, we do not
have any other information regarding the nature of the violations. Through this
procedure, we collect over 2M comments removed by moderators of 100 different
Reddit communities, and publicly release the data. Working with this dataset of
removed comments, we identify 8 macro norms---norms that are widely enforced on
most parts of Reddit. We extract these macro norms by employing a hybrid
approach---classification, topic modeling, and open-coding---on comments
identified to be norm violations within at least 85 out of the 100 study
subreddits. Finally, we label over 40K Reddit comments removed by moderators
according to the specific type of macro norm being violated, and make this
dataset publicly available. By breaking down a collection of removed comments
into more granular types of macro norm violation, our dataset can be used to
train more nuanced machine learning classifiers for online moderation.
