Crowd characterization for crowd management using social media data in city events

Abstract

Large-scale events are becoming more frequent in contemporary cities, increasing the need for novel methods and tools that can provide relevant stakeholders with quantitative and qualitative insights about attendees’ characteristics. In this work, we investigate how social media can be used to provide such insights. First, we screen a set of factors that characterize crowd behavior and introduce a set of proxies derived from social media data. We characterize the crowd in two city-scale events, Sail 2015 and King’s Day 2016, analyzing several properties of their attendees, including demographics, city-role, crowd temporal distribution, social media post locations, Point of Interest (PoI.) preferences, and word use. We show that it is possible to characterize crowds in city-scale events using social media data, thus paving the way for new real-time applications on crowd monitoring and management for city-scale events.

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