Toward a Critical Toponymy Framework for Named Entity Recognition: A
  Case Study of Airbnb in New York City
Mikael Brunila Jack LaViolette Sky CH-Wang Priyanka Verma Clara Féré Grant McKenzie
Critical toponymy examines the dynamics of power, capital, and resistance
through place names and the sites to which they refer. Studies here have
traditionally focused on the semantic content of toponyms and the top-down
institutional processes that produce them. However, they have generally ignored
the ways in which toponyms are used by ordinary people in everyday discourse,
as well as the other strategies of geospatial description that accompany and
contextualize toponymic reference. Here, we develop computational methods to
measure how cultural and economic capital shape the ways in which people refer
to places, through a novel annotated dataset of 47,440 New York City Airbnb
listings from the 2010s. Building on this dataset, we introduce a new named
entity recognition (NER) model able to identify important discourse categories
integral to the characterization of place. Our findings point toward new
directions for critical toponymy and to a range of previously understudied
linguistic signals relevant to research on neighborhood status, housing and
tourism markets, and gentrification.