  Bots are automated social media users that can be used to amplify
(mis)information and sow harmful discourse. In order to effectively influence
users, bots can be generated to reproduce human user behavior. Indeed, people
tend to trust information coming from users with profiles that fit roles they
expect to exist, such as users with gender role stereotypes. In this work, we
examine differences in the types of identities in profiles of human and bot
accounts with a focus on combinations of identities that represent gender role
stereotypes. We find that some types of identities differentiate between human
and bot profiles, confirming this approach can be a useful in distinguishing
between human and bot accounts on social media. However, contrary to our
expectations, we reveal that gender bias is expressed more in human accounts
than bots overall. Despite having less gender bias overall, we provide examples
of identities with strong associations with gender identities in bot profiles,
such as those related to technology, finance, sports, and horoscopes. Finally,
we discuss implications for designing constructive social media bot detection
training materials.
