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Reading the city through its neighbourhoods: Deep text embeddings of Yelp reviews as a basis for determining similarity and change
This paper develops novel methods for using Yelp reviews as a window into the collective representations of a city and its neighbourhoods. Basing analysis on social media data such as Yelp is a challenging task because review data is highly sparse and direct analysis may fail to uncover hidden trends. To this end, we propose a deep autoencoder approach for embedding the language of neighbourhood-based business reviews into a reduced dimensional space that facilitates similarity comparison ofdoi:10.31235/osf.io/8jbvg fatcat:mndii3ucvfdtpcedj4jqr7scg4