Date of Original Version

10-2010

Type

Conference Proceeding

Rights Management

c 2010 Association for Computational Linguistics

Abstract or Description

The rapid growth of geotagged social media raises new computational possibilities for investigating geographic linguistic variation. In this paper, we present a multi-level generative model that reasons jointly about latent topics and geographical regions. High-level topics such as “sports” or “entertainment” are rendered differently in each geographic region, revealing topic-specific regional distinctions. Applied to a new dataset of geotagged microblogs, our model recovers coherent topics and their regional variants, while identifying geographic areas of linguistic consistency. The model also enables prediction of an author’s geographic location from raw text, outperforming both text regression and supervised topic models.

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Published In

Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing, 1277-1287.