Abstract:Twitter geolocation is useful for various purposes, including tracking COVID-19 perceptions, analyzing political trends, and managing natural disasters. However, accurately predicting geolocations based on tweet content remains a challenge. In the past, machine learning approaches have tried to solve this problem by training prediction models on previously seen data, but these models often struggle to generalize to unseen places. To overcome these limitations, in this work we present a framework based on Natur… Show more
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