Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Location-based Recommendations, Geosocial Networks and Geoadvertising

Abstract

The amount of publicly available geo-referenced data has seen a dramatic explosion over the past few years. Human activity generates data and traces that are often transparently annotated with location and contextual information. At the same time, it has become easier than ever to collect and combine rich and diverse location information. For instance, in the context of geoadvertising, the use of geosocial data for targeted marketing is receiving significant attention from a wide spectrum of companies and organizations. With the advent of smartphones and online social networks, a multi-billion dollar industry that utilizes geosocial data for advertising and marketing has emerged. Geotagged social-media posts, GPS traces, data from cellular antennas and WiFi access points are used on a wide scale to directly access people for advertising, recommendations, marketing, and group purchases. Exploiting this torrent of geo-referenced data provides a tremendous potential to materially improve existing recommendation services and offer novel ones, with clear benefits in many domains, including social networks, marketing, and tourism. Achieving the full potential of geo-referenced data requires new technologies to collect, store, analyze and use the data. It also raises issues in the area of responsibility, accountability, transparency, fairness, adequacy (e.g. avoiding ads in improper places) and preventing misconduct. This in turn means addressing many core challenges and combining ideas and techniques from various research communities, such as recommender systems, data management, geographic information systems, social network analytics and text mining. By bringing together researchers and practitioners from these communities, the LocalRec workshop aims to provide a unique forum for discussing in depth and collecting feedback about challenges, opportunities, novel techniques and applications related to location-based recommendation, geosocial networks and geoadvertising.