Quantifying crowd size with mobile phone and Twitter data

Author:

Botta Federico12,Moat Helen Susannah2,Preis Tobias2

Affiliation:

1. Centre for Complexity Science, Warwick Business School, University of Warwick, Coventry CV4 7AL, UK

2. Data Science Lab, Behavioural Science, Warwick Business School, University of Warwick, Coventry CV4 7AL, UK

Abstract

Being able to infer the number of people in a specific area is of extreme importance for the avoidance of crowd disasters and to facilitate emergency evacuations. Here, using a football stadium and an airport as case studies, we present evidence of a strong relationship between the number of people in restricted areas and activity recorded by mobile phone providers and the online service Twitter . Our findings suggest that data generated through our interactions with mobile phone networks and the Internet may allow us to gain valuable measurements of the current state of society.

Publisher

The Royal Society

Subject

Multidisciplinary

Reference33 articles.

1. Simulating dynamical features of escape panic

2. ESTIMATION OF THE NUMBER OF PEOPLE IN A DEMONSTRATION

3. Privacy preserving crowd monitoring: counting people without people models or tracking;Chan AB;IEEE Conf. on Computer Vision and Pattern Recognition,2008

4. Kong D Gray D Tao H. 2006 A viewpoint invariant approach for crowd counting. 18th Int. Conf. on Pattern Recognition vol. 3 pp. 1187–1190. (doi:10.1109/ICPR.2006.197)

5. Predicting the Present with Google Trends

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