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Information propagation in social networks during crises: A structural framework.

Pohl, D. and Bouchachia, A., 2015. Information propagation in social networks during crises: A structural framework. In: Król, D., Fay, Damien and Gabrys, Bogdan, eds. Propagation Phenomena in Real World Networks. Switzerland: Springer, 293 - 309.

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DOI: 10.1007/978-3-319-15916-4_12

Abstract

In crisis situations like riots, earthquakes, storms, etc. information plays a central role in the process of organizing interventions and decision making. Due to their increasing use during crises, social media (SM) represents a valuable source of information that could help obtain a full picture of people needs and concerns. In this chapter, we highlight the importance of SM networks in crisis management (CM) to show how information is propagated through. The chapter also summarizes the current state of research related to information propagation in SMnetworks during crises. In particular three classes of information propagation research categories are identified: network analysis and community detection, role and topic-oriented information propagation, and infrastructure-oriented information propagation. The chapter describes an analysis framework that deals with structural information propagation for crisismanagement purposes. Structural propagation is about broadcasting specific information obtained from social media networks to targeted sinks/receivers/hubs like emergency agencies, police department, fire department, etc. Specifically, the framework aims to identify the discussion topics, known as sub-events, related to a crisis (event) from SM contents. A brief description of techniques used to detect topics and the way those topics can be used in structural information propagation are presented.

Item Type:Book Section
ISBN:978-3-319-15915-7, 978-3-319-15916-4
Series Name:Intelligent Systems Reference Library
Issue:85
Number of Pages:364
Uncontrolled Keywords:Cascade Failures; Complex Networks; Epidemic Spreading; Information Diffusion; Intelligent Systems; Predictive Models; Propagation Phenomena; Real World Networks; Robustness of Networks; Robustness/Reliability Estimation
Group:Faculty of Science & Technology
ID Code:33860
Deposited By: Unnamed user with email symplectic@symplectic
Deposited On:21 Apr 2020 08:59
Last Modified:21 Apr 2020 08:59

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