Sherloc: a knowledge-driven algorithm for geolocating microblog messages at sub-city level. Issue 1 (2nd January 2021)

• Record Type: Journal Article
• Authors: Di Rocco, Laura; Dassereto, Federico; Bertolotto, Michela; Buscaldi, Davide; Catania, Barbara; Guerrini, Giovanna
• Is Part Of: International journal of geographical information science. Volume 35:Issue 1(2021)
• Page Start: 84
• Page End: 115
• Publication Date: 2021-01-02
• Subjects: Geographic Information Retrieval -- geolocation inference -- fine-grained geolocation -- geo-spatial knowledge; Geography -- Data processing -- Periodicals; Information storage and retrieval systems -- Periodicals; Géomatique -- Périodiques; Systèmes d'information -- Périodiques; 910.285
• DOI: 10.1080/13658816.2020.1764003
• Languages: English
• ISSNs: 1365-8816

Abstract

ABSTRACT: Many solutions for coarse geolocating of users at the time they post a message exist. However, for many important applications, like traffic monitoring and event detection, finer geolocation at the level of city neighborhoods, i.e., at a sub-city level, is needed. Data-driven approaches often do not guarantee good accuracy and efficiency due to the higher number of sub-city level positions to be estimated and the low availability of balanced and large training sets. We claim that external information sources overcome limitations of data-driven approaches in achieving good accuracy for sub-city level geolocation and we present a knowledge-driven approach achieving good results once the reference area of a message is known. Our algorithm, called Sherloc, exploits toponyms in the message, extracts their semantic from a geographic gazetteer, and embeds them into a metric space that captures the semantic distance among them. We identify the semantically closest toponyms to a message and then cluster them with respect to their spatial locations. Sherloc requires no prior training, it can infer the location at sub-city level with high accuracy, and it is not limited to geolocating on a fixed spatial grid.