Crowd Characterization Using Social Media Data in City-Scale Events for Crowd Management

Large-scale events are becoming common in contemporary cities. There is therefore an increased need for novel methods and tools that can provide relevant stakeholders with quantitative and qualitative insights about attendees’ behaviour. In this work the authors investigate how social media can be used to provide such insights. The authors screen out a set of factors that characterize crowd behaviour, and describe a set of proxies derived from social media data. The authors characterize the crowd in two city-scales events, Sail 2015 and Kingsday 2016, analyzing several properties of their attendees, including demographics, city-role, social media posts coordinate, Point of Interest (PoI) preferences, and word use. The authors 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.

• Supplemental Notes:
  • This paper was sponsored by TRB committee ABJ30 Standing Committee on Urban Transportation Data and Information Systems.
• Authors:
  • Gong, Vincent X
  • Daamen, Winnie
  • Bozzon, Alessandro
  • Hoogendoorn, Serge
• Conference:
  • Transportation Research Board 97th Annual Meeting
  • Location: Washington DC, United States
  • Date: 2018-1-7 to 2018-1-11
• Date: 2018

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; Maps; References; Tables;
• Pagination: 23p

Subject/Index Terms

• TRT Terms: Cities; Classification; Crowds; Data mining; Demographics; Social media; Special events
• Uncontrolled Terms: Characterization
• Subject Areas: Data and Information Technology; Pedestrians and Bicyclists; Planning and Forecasting;

Filing Info

• Accession Number: 01657036
• Record Type: Publication
• Report/Paper Numbers: 18-04207
• Files: TRIS, TRB, ATRI
• Created Date: Jan 23 2018 9:29AM