Publikation

Twitter Geolocation Prediction using Neural Networks

Philippe Thomas, Leonhard Hennig

In: Proceedings of the International Conference of the German Society for Computational Linguistics and Language Technology. International Conference of the German Society for Computational Linguistics and Language Technology (GSCL-17) September 13-14 Berlin Germany GSCL 9/2017.

Abstrakt

Knowing the location of a user is important for several use cases, such as location specific recommendations, demographic analysis, or monitoring of disaster outbreaks. We present a bottom up study on the impact of text- and metadata-derived contextual features for Twitter geolocation prediction. The final model incorporates individual types of tweet information and achieves state-of-the-art performance on a publicly available test set. The source code of our implementation, together with individual models, is freely available at http://www.dfki.de/lt

Projekte

geolocation-prediction-twitter.pdf (pdf, 89 KB)

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence