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Individuals signal aspects of their identity and beliefs through linguisticchoices. Studying these choices in aggregate allows us to examine large-scaleattitude shifts within a population. Here, we develop computational methods tostudy word choice within a sociolinguistic lexical variable -- alternate wordsused to express the same concept -- in order to test for change in the UnitedStates towards sexuality and gender. We examine two variables: i) referents tosignificant others, such as the word "partner" and ii) referents to anindefinite person, both of which could optionally be marked with gender. Thelinguistic choices in each variable allow us to study increased rates ofacceptances of gay marriage and gender equality, respectively. In longitudinalanalyses across Twitter and Reddit over 87M messages, we demonstrate thatattitudes are changing but that these changes are driven by specificdemographics within the United States. Further, in a quasi-causal analysis, weshow that passages of Marriage Equality Acts in different states are drivers oflinguistic change.

Using Sociolinguistic Variables to Reveal Changing Attitudes Towards Sexuality and Gender