Citation

Bateman G, Abdel Haleem H, Majumdar A. Case Stud. Transp. Policy 2021; 9(3): 1015-1025.

Copyright

(Copyright © 2021, World Conference on Transport Research Society, Publisher Elsevier Publishing)

DOI

10.1016/j.cstp.2021.05.003

PMID

unavailable

Abstract

Terrorist attacks, and other short-scale emergencies such as active shooting events, have the potential to cause major loss of life they occur in passenger transportation terminals. Regulations often require airport authorities to be prepared for these events, but there is a lack of empirical data available to enhance response plans. Recently, there has been significant interest on how user-generated content available on social media platforms could aid with management and planning in response to emergencies. However, little of this has focused on active shooting events in particular. This paper uses a case study approach to analyse the content of social media posts to evaluate their potential to aid with situational awareness during the response phase of short-scale emergency events. Alongside a literature review conducted into this topic, this paper details the results of the analysis of 131,600 Twitter posts related to the case study active shooting event - which occurred in 2017 at Fort-Lauderdale Hollywood airport in Florida. Qualitative content analysis, and two machine learning algorithms - a Support Vector Machine, and a Latent Dirichlet Allocation model were used to categorise the tweets produced in relation to this event.

RESULTS indicate that the majority of tweets produced either simply stated that the event had occurred, or were emotional in nature, expressing worry or prayers for victims. Very few posts detailing behavioural responses of individuals involved in the event were identified. Thus, it is suggested that social media data would not be of particular use to improving situational awareness during response to short-scale emergency events in transportation terminals. Instead, social media may be of more use for information dissemination or conversations and coordination purposes during the preparation, recovery or mitigation phases of an emergency event.

Language: en

Keywords

Active shooting; Airport; Emergency management; Machine learning; Social media