Abstract: We propose a Hidden-Markov-based model integrating tweet content and user movement history to geotag tweets. We build language models for different regions and movement-based priors from users’ GPS traces. The HMM fuses content and movement features, outperforming content-only baselines on Twitter datasets.
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