The laws of "LOL": Computational approaches to sociolinguistic variation in online discussions

When speaking or writing, a person often chooses one form of language over another based on social constraints, including expectations in a conversation, participation in a global change, or expression of underlying attitudes. Sociolinguistic variation (e.g. choosing "going" versus "goin'") can reveal consistent social differences such as dialects and consistent social motivations such as audience design. While traditional sociolinguistics studies variation in spoken communication, computational sociolinguistics investigates written communication on social media. The structured nature of online discussions and the diversity of language patterns allow computational sociolinguists to test highly specific hypotheses about communication, such different configurations of listener "audience." Studying communication choices in online discussions sheds light on long-standing sociolinguistic questions that are hard to tackle, and helps social media platforms anticipate their members' complicated patterns of participation in conversations. To that end, this thesis explores open questions in sociolinguistic research by quantifying language variation patterns in online discussions. I leverage the "birds-eye" view of social media to focus on three major questions in sociolinguistics research relating to authors' participation in online discussions. First, I test the role of conversation expectations in the context of content bans and crisis events, and I show that authors vary their language to adjust to audience expectations in line with community standards and shared knowledge. Next, I investigate language change in online discussions and show that language structure, more than social context, explains word adoption. Lastly, I investigate the expression of social attitudes among multilingual speakers, and I find that such attitudes can explain language choice when the attitudes have a clear social meaning based on the discussion context. This thesis demonstrates the rich opportunities that social media provides for addressing sociolinguistic questions and provides insight into how people adapt to the communication affordances in online platforms.Ph.D