382 research outputs found
A Hierarchical Location Prediction Neural Network for Twitter User Geolocation
Accurate estimation of user location is important for many online services.
Previous neural network based methods largely ignore the hierarchical structure
among locations. In this paper, we propose a hierarchical location prediction
neural network for Twitter user geolocation. Our model first predicts the home
country for a user, then uses the country result to guide the city-level
prediction. In addition, we employ a character-aware word embedding layer to
overcome the noisy information in tweets. With the feature fusion layer, our
model can accommodate various feature combinations and achieves
state-of-the-art results over three commonly used benchmarks under different
feature settings. It not only improves the prediction accuracy but also greatly
reduces the mean error distance.Comment: Accepted by EMNLP 201
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