  Many openly non-binary gender individuals participate in social networks.
However, the relationship between gender and online interactions is not well
understood, which may result in disparate treatment by large language models.
We investigate individual identity on Twitter, focusing on gender expression as
represented by users chosen pronouns. We find that non-binary groups tend to
receive less attention in the form of likes and followers. We also find that
nonbinary users send and receive tweets with above-average toxicity. The study
highlights the importance of considering gender as a spectrum, rather than a
binary, in understanding online interactions and expression.

Social and Information Networks