title: Diffusion of lexical change in social media.
abstract: Computer-mediated communication is driving fundamental changes in the nature of written language. We investigate these changes by statistical analysis of a dataset comprising 107 million Twitter messages (authored by 2.7 million unique user accounts). Using a latent vector autoregressive model to aggregate across thousands of words, we identify high-level patterns in diffusion of linguistic change over the United States. Our model is robust to unpredictable changes in Twitter's sampling rate, and provides a probabilistic characterization of the relationship of macro-scale linguistic influence to a set of demographic and geographic predictors. The results of this analysis offer support for prior arguments that focus on geographical proximity and population size. However, demographic similarity - especially with regard to race - plays an even more central role, as cities with similar racial demographics are far more likely to share linguistic influence. Rather than moving towards a single unified "netspeak" dialect, language evolution in computer-mediated communication reproduces existing fault lines in spoken American English.
authors.affiliation: School of Interactive Computing, Georgia Institute of Technology, Atlanta, Georgia, United States of America.
authors.forename: Jacob
authors.initials: J
authors.lastname: Eisenstein
authors.affiliation: School of Computer Science, University of Massachusetts, Amherst, Massachusetts, United States of America.
authors.forename: Brendan
authors.initials: B
authors.lastname: O'Connor
authors.affiliation: School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.
authors.forename: Noah A
authors.initials: NA
authors.lastname: Smith
authors.affiliation: School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.
authors.forename: Eric P
authors.initials: EP
authors.lastname: Xing
mesh_terms: D005006:Ethnicity; D005843:Geography; D006801:Humans; D015233:Models, Statistical; D061108:Social Media; D009626:Terminology as Topic; D014481:United States / Q000208:ethnology; D014825:Vocabulary