  Content has historically been the primary lens used to study language in
online communities. This paper instead focuses on the linguistic style of
communities. While we know that individuals have distinguishable styles, here
we ask whether communities have distinguishable styles. Additionally, while
prior work has relied on a narrow definition of style, we employ a broad
definition involving 262 features to analyze the linguistic style of 9 online
communities from 3 social media platforms discussing politics, television and
travel. We find that communities indeed have distinct styles. Also, style is an
excellent predictor of group membership (F-score 0.952 and Accuracy 96.09%).
While on average it is statistically equivalent to predictions using content
alone, it is more resilient to reductions in training data.
