Affiliation:
1. The George Washington University, USA
Abstract
In this paper we identify a method, which rapidly analyzes vast amounts of data present in social media in order to forecast crowd sizes. Based upon comparative analysis of related literature, a conceptual model is proposed and research conducted to develop capabilities to forecast mass collective action behavior such as crowd formation using Social Network Analysis (SNA) tools applied to online social media. We demonstrate that a simple model of online social network parameters can produce situation awareness of crowd sizes in much the same way that radar sensors can produce situation awareness of air traffic density. A prototype online social media ‘radar' sensor system is developed and tested in a pilot study with a dataset of tweets gathered regarding the Occupy Wall Street movement. Further work is suggested which could provide anticipated crowd location, movement and intent in addition to size.