A Neural Model for User Geolocation and Lexical Dialectology

ACL 2017  ·  Afshin Rahimi, Trevor Cohn, Timothy Baldwin ·

We propose a simple yet effective text- based user geolocation model based on a neural network with one hidden layer, which achieves state of the art performance over three Twitter benchmark geolocation datasets, in addition to producing word and phrase embeddings in the hidden layer that we show to be useful for detecting dialectal terms. As part of our analysis of dialectal terms, we release DAREDS, a dataset for evaluating dialect term detection methods.

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