FewUser: Few-Shot Social User Geolocation via Contrastive Learning

arXiv:2404.08662v1 Announce Type: cross
Abstract: To address the challenges of scarcity in geotagged data for social user geolocation, we propose FewUser, a novel framework for Few-shot social User geolocation. We incorporate a contrastive learning strategy between users and locations to improve geolocation performance with no or limited training data. FewUser features a user representation module that harnesses a pre-trained language model (PLM) and a user encoder to process and fuse diverse social media inputs effectively. To bridge the gap between …

abstract arxiv challenges cs.ir cs.lg cs.si data features few-shot framework geolocation locations novel performance social strategy training training data type via