1.Centers for Disease Control and Prevention. Disaster Training and Response. Preparedness and Response for Public Health Disasters Web site. https://www.cdc.gov/nceh/hsb/disaster/training.htm. Published 2018. Updated May 8, 2018. (Accessed December 13, 2018).
5.Finch, KC, Snook, KR, Duke, CH, et al.Public health implications of social media use during natural disasters, environmental disasters, and other environmental concerns. Nat Hazards. 2016;83(1):729–760.10.1007/s11069-016-2327-8
6.Fung, IC, Tse, ZT, Fu, KW. The use of social media in public health surveillance. Western Pac surveill Response J. 2015;6(2):3–6.10.5365/wpsar.2015.6.1.019
8.Kim, J, Bae, J, Hastak, M. Emergency information diffusion on online social media during storm Cindy in US. Int J Inf Manage. 2018;40:153–165.10.1016/j.ijinfomgt.2018.02.003
9.Adams, J, Raeside, R, Khan, HTA. Research Methods for Business and Social Science Students. 2nd ed. New Delhi: Sage Publications Pvt. Ltd; 2014.
10.Wang, B, Zhuang, J. Crisis information distribution on Twitter: a content analysis of tweets during Hurricane Sandy. Nat Hazards. 2017;89(1):161–181.10.1007/s11069-017-2960-x
11.Kiatpanont, R, Tanlamai, U, Chongstitvatana, P. Extraction of actionable information from crowdsourced disaster data. J Emerg Manag. 2016;14(6):377–390.10.5055/jem.2016.0302
12.Ungvarsky, J.Sentiment Analysis. Pasadena, CA: Salem Press; 2017.
13.Abedin, B, Babar, A, Abbasi, A. Characterization of the use of social media in natural disasters: a systematic review. In: Proceedings of the 2014 IEEE Fourth International Conference on Big Data and Cloud Computing IEEE Computer Society, Sydney, Australia; 2014.10.1109/BDCloud.2014.17
14.Yu, M, Yang, C, Li, Y. Big data in natural disaster management: a review. Geosciences. 2018;8(5):165.10.3390/geosciences8050165
15.Wang, Z, Ye, X. Social media analytics for natural disaster management. Int J Geograph Inf Sci. 2018;32(1):49–72.10.1080/13658816.2017.1367003
16.Moher, D, Liberati, A, Tetzlaff, J, et al.Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6(7):e1000097.10.1371/journal.pmed.1000097
17.Rodrigueza, RC, Estuar, MRJE. Social network analysis of a disaster behavior network: an agent-based modeling approach. Paper presented at: 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM); August 28-31, 2018.
18.Wu, D, Cui, Y. Disaster early warning and damage assessment analysis using social media data and geo-location information. Decis Support Syst. 2018;111:48–59.10.1016/j.dss.2018.04.005
19.Liu, G-R, Mao, L-X, Wang, L-L, et al. Automotive prospective technology mining method based on big data content analysis. Paper presented at: 2017 IEEE 2nd International Conference on Cloud Computing and Big Data Analysis (ICCCBDA); April 28-30, 2017.
20.Deng, Q, Liu, Y, Zhang, H, et al.A new crowdsourcing model to assess disaster using microblog data in typhoon Haiyan. Nat Hazards. 2016;84(2):1241–1256.10.1007/s11069-016-2484-9
21.Resch, B, Uslander, F, Havas, C. Combining machine-learning topic models and spatiotemporal analysis of social media data for disaster footprint and damage assessment. Cartogr Geogr Inf Sci. 2018;45(4):362–376.10.1080/15230406.2017.1356242
22.Cervone, G, Sava, E, Huang, Q, et al.Using Twitter for tasking remote-sensing data collection and damage assessment: 2013 Boulder flood case study. Int J Remote Sens. 2016;37(1):100–124.10.1080/01431161.2015.1117684
23.Avvenuti, M, Cresci, S, Del Vigna, F, Tesconi, M. Impromptu crisis mapping to prioritize emergency response. Computer. 2016;49(5):28–37.10.1109/MC.2016.134
24.Avvenuti, M, Cimino, MG, Cresci, S, et al.A framework for detecting unfolding emergencies using humans as sensors. Springerplus. 2016;5:43.10.1186/s40064-016-1674-y
25.Kim, J, Hastak, M. Social network analysis: characteristics of online social networks after a disaster. Int J Inf Manag. 2018;38(1):86–96.10.1016/j.ijinfomgt.2017.08.003
26.Sutton, J, League, C, Sellnow, TL, Sellnow, DD. Terse messaging and public health in the midst of natural disasters: the case of the Boulder floods. Health Commun. 2015;30(2):135–143.10.1080/10410236.2014.974124
27.Tang, Z, Zhang, L, Xu, F, et al.Examining the role of social media in California’s drought risk management in 2014. Nat Hazards. 2015;79(1):171–193.10.1007/s11069-015-1835-2
28.Scott, KK, Errett, NA. Content, accessibility, and dissemination of disaster information via social media during the 2016 Louisiana floods. J Public Health Manag Pract. 2018;24(4):370–379.10.1097/PHH.0000000000000708
29.Albris, K. The switchboard mechanism: how social media connected citizens during the 2013 floods in Dresden. J ContingCrisis Manag. 2018;26(3):350–357.10.1111/1468-5973.12201
30.Wang, Z, Ye, X, Tsou, M-H. Spatial, temporal, and content analysis of Twitter for wildfire hazards. Nat Hazards. 2016;83(1):523–540.10.1007/s11069-016-2329-6
31.Grasso, V, Crisci, A. Codified hashtags for weather warning on Twitter: an Italian case study. PLoS Curr. 2016;8 pii: ecurrents.dis.967e71514ecb92402eca3bdc9b789529.
32.Brandt, HM, Turner-McGrievy, G, Friedman, DB, et al.Examining the role of Twitter in response and recovery during and after historic flooding in South Carolina. J Public Health Manag Pract. 2018. doi: 10.1097/PHH.0000000000000841.
33.Ramirez Plascencia, D, Ramirez Plascencia, J. e-Solidarity and exchange: the role of social media in public mexican response to Hurricane Patricia in 2015. Int J Public Admin Digit Age. 2017;4(3):1–10.10.4018/IJPADA.2017070101
34.Yi, CJ, Kuri, M. The prospect of online communication in the event of a disaster. J Risk Res. 2016;19(7):951–963.10.1080/13669877.2015.1115424
35.Kaufhold, M-A, Reuter, C. The self-organization of digital volunteers across social media: the case of the 2013 European floods in Germany. J Homel Secur Emerg Manag. 2016;13(1):137–166.
36.Li, L, Zhang, Q, Tian, J, et al.Characterizing information propagation patterns in emergencies: a case study with Yiliang Earthquake. Int J Inf Manag. 2018;38(1):34–41.10.1016/j.ijinfomgt.2017.08.008
37.David, CC, Ong, JC, Legara, EF. Tweeting Supertyphoon Haiyan: evolving functions of Twitter during and after a disaster event. PLoS One. 2016;11(3):e0150190.10.1371/journal.pone.0150190
38.Cooper, GP Jr, Yeager, V, Burkle, FM Jr, et al.Twitter as a potential disaster risk reduction tool. Part III: evaluating variables that promoted regional Twitter use for at-risk populations during the 2013 Hattiesburg F4 tornado. PLoS Curr Disast. 2015;7.
39.Huang, Q, Xiao, Y. Geographic situational awareness: mining tweets for disaster preparedness, emergency response, impact, and recovery. Isprs Int J Geo-Inf. 2015;4(3):1549–1568.10.3390/ijgi4031549
40.Pohl, D, Bouchachia, A, Hellwagner, H. Online indexing and clustering of social media data for emergency management. Neurocomputing. 2016;172:168–179.10.1016/j.neucom.2015.01.084
41.Stephenson, J, Vaganay, M, Coon, D, et al.The role of Facebook and Twitter as organisational communication platforms in relation to flood events in Northern Ireland. J Flood Risk Manag. 2018;11(3):339–350.10.1111/jfr3.12329
42.Schiavo, R. Health Communiation from Theory to Practice San Francisco, CA: John Wiley & Sons; 2007.
43.Valente, TW. Social Networks and Health: Models, Methods, and Applications. New York: University Press Scholarship Online; 2010.10.1093/acprof:oso/9780195301014.001.0001
44.Juliadi, R, Ardani, EG. The interactivity of twitwar among social media influencer and followers on Twitter. Int J Multicul Multireligious Underst. 2019(7):110.
45.Nath, RN, Priya, N, Rene Robin, CR. A social media content based location and situation analysis model for disaster management. Int J Public Admin Digital Age. 2017;4(3):42–52.10.4018/IJPADA.2017070104
46.Bai, H, Yu, G. A Weibo-based approach to disaster informatics: incidents monitor in post-disaster situation via Weibo text negative sentiment analysis. Nat Hazards. 2016;83(2):1177–1196.10.1007/s11069-016-2370-5
47.Yuan, F, Liu, R. Feasibility study of using crowdsourcing to identify critical affected areas for rapid damage assessment: Hurricane Matthew case study. Int J Disaster Risk Reduct. 2018;28:758–767.10.1016/j.ijdrr.2018.02.003
48.de Albuquerque, JP, Herfort, B, Brenning, A, et al.A geographic approach for combining social media and authoritative data towards identifying useful information for disaster management. Int J Geograph Inf Sci. 2015;29(4):667–689.10.1080/13658816.2014.996567
49.Kryvasheyeu, Y, Chen, H, Obradovich, N, et al.Rapid assessment of disaster damage using social media activity. Sci Adv. 2016;2(3):e1500779.10.1126/sciadv.1500779
50.Comunello, F, Parisi, L, Lauciani, V, et al.Tweeting after an earthquake: user localization and communication patterns during the 2012 Emilia seismic sequence. Ann Geophys. 2016;59(5).
51.Zahra, K, Ostermann, FO, Purves, RS. Geographic variability of Twitter usage characteristics during disaster events. Geo Spat Inf Sci. 2017;20(3):231–240.10.1080/10095020.2017.1371903
52.Zou, L, Lam, NSN, Cai, H, et al.Mining Twitter data for improved understanding of disaster resilience. Ann Am Assoc Geogr. 2018;108(5):1422–1441.
53.Tim, Y, Pan, SL, Ractham, P, et al.Digitally enabled disaster response: the emergence of social media as boundary objects in a flooding disaster. Inf Syst J. 2017;27(2):197–232.10.1111/isj.12114
54.Gul, S, Shah, TA, Ahad, M, et al.Twitter sentiments related to natural calamities Analysing tweets related to the Jammu and Kashmir floods of 2014. Electron Library. 2018;36(1):38–54.10.1108/EL-12-2015-0244
55.Ragini, JR, Anand, PMR, Bhaskar, V. Big data analytics for disaster response and recovery through sentiment analysis. Int J Inf Manag. 2018;42:13–24.10.1016/j.ijinfomgt.2018.05.004
56.Andrews, S, Gibson, H, Domdouzis, K, et al.Creating corroborated crisis reports from social media data through formal concept analysis. J Intell Inf Syst. 2016;47(2):287–312.10.1007/s10844-016-0404-9
57.Xu, Z, Zhang, H, Sugumaran, V, et al.Participatory sensing-based semantic and spatial analysis of urban emergency events using mobile social media. EURASIP J Wirel Commun Netw. 2016;44. doi: 10.1186/s13638-016-0553-0.
58.Sherchan, W, Pervin, S, Butler, CJ, et al.Harnessing Twitter and Instagram for disaster management. IBM J Res Dev. 2017;61(6):8:1–8:12.10.1147/JRD.2017.2729238
59.Avvenuti, M, Cresci, S, La Polla, MN, et al.Nowcasting of earthquake consequences using big social data. IEEE Internet Comput. 2017;21(6):37–45.10.1109/MIC.2017.4180834
60.Fohringer, J, Dransch, D, Kreibich, H, et al.Social media as an information source for rapid flood inundation mapping. Nat Hazards Earth Syst Sci. 2015;15(12):2725–2738.10.5194/nhess-15-2725-2015
61.Li, Z, Wang, C, Emrich, CT, et al.A novel approach to leveraging social media for rapid flood mapping: a case study of the 2015 South Carolina floods. Cartogr Geogr Inf Sci. 2017;45(2):97–110.10.1080/15230406.2016.1271356
62.Wang, Y, Taylor, JE. Coupling sentiment and human mobility in natural disasters: a Twitter-based study of the 2014 South Napa Earthquake. Nat Hazards. 2018;92(2):907–925.10.1007/s11069-018-3231-1
64.Federal Emergency Management Agency. Introduction to Crisis, Disaster, and Risk Management Concepts. 2018:25.
65.Lee, H, Oh, HJ. Normative mechanism of rumor dissemination on Twitter. Cyberpsychol Behav Soc Netw. 2017;20(3):164–171.10.1089/cyber.2016.0447
66.Harris, JK, Mueller, NL, Snider, D. Social media adoption in local health departments nationwide. Am J Public Health. 2013;103(9):1700–1707.10.2105/AJPH.2012.301166
67.Liang, H, Shen, F, Fu, K-w. Privacy protection and self-disclosure across societies: a study of global Twitter users. New Media Soc. 2016;19(9):1476–1497.10.1177/1461444816642210
68.Fu, K-w, White, J, Chan, Y-y, et al.Enabling the disabled: media use and communication needs of people with disabilities during and after the Sichuan earthquake in China. Int J Emerg Manag. 2010;7(1):75–87.10.1504/IJEM.2010.032046
69.Jackson, AM, Mullican, LA, Tse, ZTH, Yin, J, et al.Unplanned closure of public schools in Michigan, 2015-2016: Cross-sectional study on rurality and digital data harvesting. J Sch Health. 2020. In Press.