Social sensing: towards social media as a sensor for resilience in power systems and other critical infrastructures

References

• Barker, K., Lambert, J. H., Zobel, C. W., Tapia, A. H., Albert, L., Nicholson, C. D., Caragea, C., Barker, K., Lambert, J. H., Zobel, C. W., Tapia, A. H., Albert, L., Nicholson, C. D., & Defining, C. C. (2017). Defining resilience analytics for interdependent cyber-physical-social networks. Sustainable and Resilient Infrastructure, 9689(March), 1–9.
   Google Scholar
• Bodnar, T., Dering, M. L., Tucker, C., & Hopkinson, K. M. (2017). Using large-scale social media networks as a scalable sensing system for modeling real-time energy utilization patterns. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 47(10), 2627–2640.
   Web of Science ®Google Scholar
• Chou, -C.-C., & Tseng, S.-M. (2010). Collection and analysis of Critical Infrastructure interdependency relationships. Journal of Computing in Civil Engineering, 24(6), 539–547.
   Web of Science ®Google Scholar
• Committee on Increasing National Resilience to Hazards and Disasters. (2012). Disaster resilience: A national imperative. Washington, DC: The National Academies Press.
   Google Scholar
• Dashti, S., Palen, L., Heris, M. P., Anderson, K. M., Anderson, S., & Anderson, T. J. (2014). Supporting disaster reconnaissance with social media data: A design-oriented case study of the 2013 Colorado floods. In Proceedings of the 11th international ISCRAM conference, number May (pp. 632–641). Pennsylvania: University Park.
   Google Scholar
• Duenas-Osorio, L., & Kwasinski, A. (2012). Quantification of lifeline system interdependencies after the 27 February 2010 Mw 8.8 offshore Maule, Chile, earthquake. Earthquake Spectra, 28, 581–603.
   Web of Science ®Google Scholar
• Electricity Consumers Resource Council. (2004). The economic impacts of the august 2003 blackout.
   Google Scholar
• Gasser, P., Lustenberger, P., Cinelli, M., Kim, W., Spada, M., Burgherr, P., ... Sun, T. Y. (2019). A review on resilience assessment of energy systems. Sustainable and Resilient Infrastructure, 1–27. Retrieved from https://www.tandfonline.com/doi/full/10.1080/23789689.2019.1610600
   Google Scholar
• Gilrein, E. J., Carvalhaes, T. M., Markolf, S. A., Chester, M. V., Allenby, B. R., & Garcia, M. (2019). Concepts and practices for transforming infrastructure from rigid to adaptable. Sustainable and Resilient Infrastructure, 1–22. Retrieved from https://doi.org/10.1080/23789689.2019.1599608
   Web of Science ®Google Scholar
• Guan, X., & Chen, C. (2014). Using social media data to understand and assess disasters. Natural Hazards, 74(2), 837–850.
   Web of Science ®Google Scholar
• Guan, X., Chen, C., & Work, D. (2016). Tracking the evolution of infrastructure systems and mass responses using publically available data. PloS One, 11(12), 1–17.
   Web of Science ®Google Scholar
• Guidotti, R., Chmielewski, H., Unnikrishnan, V., Gardoni, P., McAllister, T., & van de Lindt, J. (2016). Modeling the resilience of critical infrastructure: The role of network dependencies. Sustainable and Resilient Infrastructure, 1(3–4), 153–168.
   PubMed Web of Science ®Google Scholar
• Hyndman, R., & Athanasopoulos, G. (2018). Forecasting: Principles and practice (2 ed.). Melbourne, Australia: OTexts.
   Google Scholar
• Koliou, M., van de Lindt, J. W., McAllister, T. P., Ellingwood, B. R., Dillard, M., & Cutler, H. (2018). State of the research in community resilience: Progress and challenges. Sustainable and Resilient Infrastructure, 1–21. Retrieved from https://www.tandfonline.com/doi/full/10.1080/23789689.2017.1418547
   Web of Science ®Google Scholar
• Kryvasheyeu, Y., Chen, H., Obradovich, N., Moro, E., Van Hentenryck, P., Fowler, J., & Cebrian, M. (2016). Rapid assessment of disaster damage using social media activity. Science Advances, 2(3), e1500779–e1500779.
   PubMed Web of Science ®Google Scholar
• Kumar, S., Morstatter, F., & Liu, H. (2014). Twitter Data Analytics. New York: Springer.
   Google Scholar
• Kunz, M., Mühr, B., Kunz-Plapp, T., Daniell, J. E., Khazai, B., Wenzel, F., Vannieuwenhuyse, M., Comes, T., Elmer, F., Schröter, K., Fohringer, J., Münzberg, T., Lucas, C., & Zschau, J. (2013). Investigation of superstorm Sandy 2012 in a multi-disciplinary approach. Natural Hazards and Earth System Sciences, 13(10), 2579–2598.
   Web of Science ®Google Scholar
• LaLone, N., Tapia, A., Zobel, C., Caraega, C., Neppalli, V. K., & Halse, S. (2017). Embracing human noise as resilience indicator: Twitter as power grid correlate. Sustainable and Resilient Infrastructure, 9689, 1–10.
   Google Scholar
• Loper, E., & Bird, S. (2006). NLTK: The Natural Language Toolkit. In Proceedings of the COLING/ACL 2006 on interactive presentation sessions, (pp 69–72). Sydney, Australia.
   Google Scholar
• McDaniels, T., Chang, S., Peterson, K., Mikawoz, J., & Reed, D. (2007). Empirical framework for characterizing infrastructure failure interdependencies. Journal of Infrastructure Systems, 13(3), 175–184.
   Web of Science ®Google Scholar
• Mendonça, D., & Wallace, W. A. (2006). Impacts of the 2001 world trade center attack on New York city critical infrastructures. Journal of Infrastructure Systems, 12(4), 260–270.
   Web of Science ®Google Scholar
• Milanovic, J. V., & Zhu, W. (2017). Modelling of interconnected critical infrastructure systems using complex network theory. IEEE Transactions on Smart Grid, 3053(c), 1–1.
   Google Scholar
• Murthy, D., & Gross, A. J. (2017). Social media processes in disasters: Implications of emergent technology use. Social Science Research, 63, 356–370.
   PubMed Web of Science ®Google Scholar
• Nazer, T. H., Xue, G., Ji, Y., & Liu, H. (2017). intelligent disaster response via social media analysis - A survey. ACM SIG-KDD Explorations, 19, 1–14.
   Google Scholar
• Ouyang, M. (2014). Review on modeling and simulation of interdependent critical infrastructure systems. Reliability Engineering and System Safety, 121, 43–60.
   Web of Science ®Google Scholar
• Porter, M. (1980). An algorithm for suffix stripping. Program, 14(3), 130–137.
   Google Scholar
• Preis, T., Moat, H. S., Bishop, S. R., Treleaven, P., & Stanley, H. E. (2013). Quantifying the digital traces of hurricane sandy on flickr. Scientific Reports, 3, 3–5.
   Web of Science ®Google Scholar
• Righi, A. W., Saurin, T. A., & Wachs, P. (2015). A systematic literature review of resilience engineering: Research areas and a research agenda proposal. Reliability Engineering & System Safety, 141, 142–152.
   Web of Science ®Google Scholar
• Sharkey, T. C., Nurre, S. G., Nguyen, H., Chow, J. H., Mitchell, J. E., & Wallace, W. A. (2016). Identification and classification of restoration interdependencies in the wake of Hurricane Sandy. Journal of Infrastructure Systems, 22(1), 04015007–1–12.
   Web of Science ®Google Scholar
• Shumway, R. H., & Stoffer, D. S. (2017). Time series analysis and its applications: With R examples (4 ed.). Cham, Switzerland: Springer International Publishing.
   Google Scholar
• Uday, P., & Marais, K. (2015). Designing resilient systems-of-systems: A survey of metrics, methods, and challenges. Systems Engineering, 18(5), 491–510.
   Web of Science ®Google Scholar
• Unnikrishnan, V. U., & van de Lindt, J. W. (2016). Probabilistic framework for performance assessment of electrical power networks to tornadoes. Sustainable and Resilient Infrastructure, 1(3–4), 137–152.
   Web of Science ®Google Scholar
• Wang, H., Hovy, E., & Dredze, M. (2015). The Hurricane Sandy Twitter corpus. In AAAI workshop on the world wide web and public health intelligence, (pp. 20–24).
   Google Scholar
• Wu, F., Wang, H., & Li, Z. (2016). Interpreting traffic dynamics using ubiquitous urban data. In Proceedings of the 24th ACM SIGSPATIAL international conference on advances in Geographic Information Systems - GIS ’16, (pp. 1–4).
   Google Scholar
• Yagan, O., Qian, D., Zhang, J., & Cochran, D. (2012). Optimal allocation of interconnecting links in cyber-physical systems: interdependence, cascading failures, and robustness. IEEE Transactions on Parallel and Distributed Systems, 23(9), 1708–1721.
   Web of Science ®Google Scholar
• Yodo, N., & Wang, P. (2016). Engineering resilience quantification and system design implications: A literature survey. Journal of Mechanical Design, 138(11), 111408–1–13.
   Web of Science ®Google Scholar
• Zio, E. (2016). Challenges in the vulnerability and risk analysis of critical infrastructures. Reliability Engineering and System Safety, 152, 137–150.
   Web of Science ®Google Scholar