  Word choice is dependent on the cultural context of writers and their
subjects. Different words are used to describe similar actions, objects, and
features based on factors such as class, race, gender, geography and political
affinity. Exploratory techniques based on locating and counting words may,
therefore, lead to conclusions that reinforce culturally inflected boundaries.
We offer a new method, the DualNeighbors algorithm, for linking thematically
similar documents both within and across discursive and linguistic barriers to
reveal cross-cultural connections. Qualitative and quantitative evaluations of
this technique are shown as applied to two cultural datasets of interest to
researchers across the humanities and social sciences. An open-source
implementation of the DualNeighbors algorithm is provided to assist in its
application.
