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Predicting the geographical location of users on social networks like Twitteris an active research topic with plenty of methods proposed so far. Most of theexisting work follows either a content-based or a network-based approach. Theformer is based on user-generated content while the latter exploits thestructure of the network of users. In this paper, we propose a more genericapproach, which incorporates not only both content-based and network-basedfeatures, but also other available information into a unified model. Ourapproach, named Multi-Entry Neural Network (MENET), leverages the latestadvances in deep learning and multiview learning. A realization of MENET withtextual, network and metadata features results in an effective method forTwitter user geolocation, achieving the state of the art on two well-knowndatasets.

Twitter User Geolocation using Deep Multiview Learning