  Linguistic norms emerge in human communities because people imitate each
other. A shared linguistic system provides people with the benefits of shared
knowledge and coordinated planning. Once norms are in place, why would they
ever change? This question, echoing broad questions in the theory of social
dynamics, has particular force in relation to language. By definition, an
innovator is in the minority when the innovation first occurs. In some areas of
social dynamics, important minorities can strongly influence the majority
through their power, fame, or use of broadcast media. But most linguistic
changes are grassroots developments that originate with ordinary people. Here,
we develop a novel model of communicative behavior in communities, and identify
a mechanism for arbitrary innovations by ordinary people to have a good chance
of being widely adopted.
  To imitate each other, people must form a mental representation of what other
people do. Each time they speak, they must also decide which form to produce
themselves. We introduce a new decision function that enables us to smoothly
explore the space between two types of behavior: probability matching (matching
the probabilities of incoming experience) and regularization (producing some
forms disproportionately often). Using Monte Carlo methods, we explore the
interactions amongst the degree of regularization, the distribution of biases
in a network, and the network position of the innovator. We identify two
regimes for the widespread adoption of arbritrary innovations, viewed as
informational cascades in the network. With moderate regularization of
experienced input, average people (not well-connected people) are the most
likely source of successful innovations. Our results shed light on a major
outstanding puzzle in the theory of language change. The framework also holds
promise for understanding the dynamics of other social norms.
