Geotagging tweets to landmarks using convolutional neural networks with text and posting time
KH Lim, S Karunasekera, A Harwood, Y George
Proceedings of the 24th International Conference on Intelligent User Interfaces: Companion | ACM | Published : 2019
Geotagged tweets serve many important applications, e.g., crisis management, but only a small proportion of tweets are explicitly geotagged. We propose a Convolutional Neural Network (CNN) architecture for geotagging tweets to landmarks, based on the text in tweets and other meta information, such as posting time and source. Using a dataset of Melbourne tweets, experimental results show that our algorithm out-performed various state-of-the-art baselines.
Awarded by Singapore University of Technology and Design
This research is partly supported by the Singapore University of Technology and Design under grant SRG-ISTD-2018-140, and Defence Science and Technology, Australia.