Diffusion of Lexical Change in Social Media

作者：Eisenstein Jacob^*; O'Connor Brendan; Smith Noah A; Xing Eric P

来源：PLos One, 2014, 9(11): e113114.

DOI：10.1371/journal.pone.0113114

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.

• 出版日期2014-11-19