  Language change is a complex social phenomenon, revealing pathways of
communication and sociocultural influence. But, while language change has long
been a topic of study in sociolinguistics, traditional linguistic research
methods rely on circumstantial evidence, estimating the direction of change
from differences between older and younger speakers. In this paper, we use a
data set of several million Twitter users to track language changes in
progress. First, we show that language change can be viewed as a form of social
influence: we observe complex contagion for phonetic spellings and "netspeak"
abbreviations (e.g., lol), but not for older dialect markers from spoken
language. Next, we test whether specific types of social network connections
are more influential than others, using a parametric Hawkes process model. We
find that tie strength plays an important role: densely embedded social ties
are significantly better conduits of linguistic influence. Geographic locality
appears to play a more limited role: we find relatively little evidence to
support the hypothesis that individuals are more influenced by geographically
local social ties, even in their usage of geographical dialect markers.
