Placing User-generated Content on the Map with Confidence. Intagorn, S. & Lerman, K. In ACM GIS, 2014.
Placing User-generated Content on the Map with Confidence [pdf]Paper  abstract   bibtex   
We describe a method that predicts the location of user-generated content using textual features alone. Unlike previous methods for geotagging text documents, our proposed method is not sensitive to how we discretize space. We also discover that spatial resolu- tion has an impact on the prediction accuracy, which allows us to trade-off the spatial resolution of the predicted location against our confidence about its accuracy. Our method can be used to estimate the error in document�s predicted location, enabling us to filter out poor quality predictions. We evaluate the proposed method exten- sively on user-generated content collected from two different social media sites, Flickr and Twitter. Our evaluation examines its perfor- mance on the geotagging task and with respect to different parame- ters. We achieve state-of-the-art results for all three tasks: location prediction, error estimation and result ranking and also provide a theoretical explanation of the effect of spatial resolution factor on geotagging accuracy. Our findings provide valuable insights into the design of geotagging systems and their quality control.

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