March 2015: Graph-Based Residence Location Inference for Social Media Users

posted Mar 10, 2015, 11:20 AM by Symeon Papadopoulos
Dan Xu, Peng Cui, Wenwu Zhu, Shiqiang Yang, "Graph-Based Residence Location Inference for Social Media Users", IEEE MultiMedia, vol.21, no. 4, pp. 76-83, Oct.-Dec. 2014, doi:10.1109/MMUL.2014.62

Abstract: Location information in social media is becoming increasingly vital in applications such as election prediction, epidemic forecasting, and emergency detection. However, only a tiny proportion of users proactively share their residence locations (which can be used to approximate the locations of most user-generated content) in their profiles, and inferring the residence location of the remaining users is nontrivial. In this article, the authors propose a framework for residence location inference in social media by jointly considering social, visual, and textual information. They first propose a data-driven approach to explore the use of friendship locality, social proximity, and content proximity for geographically nearby users. Based on these observations, they then propose a location propagation algorithm to effectively infer residence location for social media users. They extensively evaluate the proposed method using a large-scale real dataset and achieve a 15 percent relative improvement over state-of-the-art approaches.