Chapter
Jun 13, 2019
ASCE International Conference on Computing in Civil Engineering 2019

Seeding Strategies in Online Social Networks for Improving Information Dissemination of Built Environment Disruptions in Disasters

Publication: Computing in Civil Engineering 2019: Data, Sensing, and Analytics

ABSTRACT

The objective of this study is to propose a seed-search algorithm and develop seeding strategies in online social networks for disseminating credible situational information regarding built environment disruptions in disasters. Rapid and extensive dissemination of credible situational information is important for disaster preparedness, response, and recovery in communities. Online social networks such as Twitter have become popular media sources among the public to share information in disasters. Due to the directed relations and fragmentations in networks, however, little is known about the ways of selecting starting nodes (a.k.a., seeds) in order to broadly and rapidly spread information online. To address this gap, this study proposes a computational approach, which is an integration of greedy algorithm and graph analysis, to capture fragmentations, identify critical seeds, and develop seeding strategies to disseminate information in online social networks. A case study of an infrastructure disruption (water release from reservoirs in Houston) during 2017 Hurricane Harvey was used to illustrate the capabilities of the proposed approach. The results indicate that seeding top 10 users is effective for distributing information to more than 80% of nodes in a network. The findings inform about strategies to better report, transmit, and gather situational information on social media, which can further enhance situation awareness and community resilience in disasters.

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ACKNOWLEDGEMENT

This material is based in part upon work supported by the National Science Foundation under Grant Number IIS-1759537. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

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Information & Authors

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Published In

Go to Computing in Civil Engineering 2019
Computing in Civil Engineering 2019: Data, Sensing, and Analytics
Pages: 487 - 494
Editors: Yong K. Cho, Ph.D., Georgia Institute of Technology, Fernanda Leite, Ph.D., University of Texas at Austin, Amir Behzadan, Ph.D., Texas A&M University, and Chao Wang, Ph.D., Louisiana State University
ISBN (Online): 978-0-7844-8243-8

History

Published online: Jun 13, 2019
Published in print: Jun 13, 2019

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Authors

Affiliations

Ph.D. Student, Zachry Dept. of Civil Engineering, Texas A&M Univ., College Station, TX 77843-3136. E-mail: [email protected]
Yucheng Jiang [email protected]
B.S. Student, Dept. of Computer Science and Engineering, Texas A&M Univ., College Station, TX 77843-3136. E-mail: [email protected]
Ali Mostafavi, Ph.D. [email protected]
Assistant Professor, Zachry Dept. of Civil Engineering, Texas A&M Univ., College Station, TX 77843-3136. E-mail: [email protected]

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