  We analyze gendered communities defined in three different ways: text, users,
and sentiment. Differences across these representations reveal facets of
communities' distinctive identities, such as social group, topic, and
attitudes. Two communities may have high text similarity but not user
similarity or vice versa, and word usage also does not vary according to a
clearcut, binary perspective of gender. Community-specific sentiment lexicons
demonstrate that sentiment can be a useful indicator of words' social meaning
and community values, especially in the context of discussion content and user
demographics. Our results show that social platforms such as Reddit are active
settings for different constructions of gender.
