  The automatic classification of Arabic dialects is an ongoing research
challenge, which has been explored in recent work that defines dialects based
on increasingly limited geographic areas like cities and provinces. This paper
focuses on a related yet relatively unexplored topic: the effects of the
geographical proximity of cities located in Arab countries on their dialectical
similarity. Our work is twofold, reliant on: 1) comparing the textual
similarities between dialects using cosine similarity and 2) measuring the
geographical distance between locations. We study MADAR and NADI, two
established datasets with Arabic dialects from many cities and provinces. Our
results indicate that cities located in different countries may in fact have
more dialectical similarity than cities within the same country, depending on
their geographical proximity. The correlation between dialectical similarity
and city proximity suggests that cities that are closer together are more
likely to share dialectical attributes, regardless of country borders. This
nuance provides the potential for important advancements in Arabic dialect
research because it indicates that a more granular approach to dialect
classification is essential to understanding how to frame the problem of Arabic
dialects identification.
