Abstract
This study sheds new light on understanding human sentiment for Winter storm Jupiter according to the whole US states and different periods based on qualitative and quantitative analyses. This study finds that Twitter users upload their tweets to share important messages for the winter storm, such as weather changes and road conditions. Next, some people think that governments use the winter storm to move people’s attention from the serious problems in their life to the weather issue. Third, people are highly interested in a temporary school or workplace closing and weather forecast channels in the winter storm week. Fourth, tweets have the most frequent keywords, such as day, ice, and today, which are related to the weather during the winter storm. Lastly, the spatial pattern of the proportion of tweets is differentiated by regions and periods.
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Aldunce, P., Beilin, R., Howden, M., Handmer, J.: Resilience for disaster risk management in a changing climate: practitioners’ frames and practices. Glob. Environ. Chang. 30, 1–11 (2015)
Bhavaraju, S.K.T., Beyney, C., Nicholson, C.: Quantitative analysis of social media sensitivity to natural disasters. Int. J. Disaster Risk Reduct 39, 101251 (2019)
Bronfman, N.C., Cisternas, P.C., Repetto, P.B., Castañeda, J.V.: Natural disaster preparedness in a multi-hazard environment: characterizing the sociodemographic profile of those better (worse) prepared. PloS One 14(4), e0214249 (2019)
Bruns, A., Liang, Y.E.: Tools and methods for capturing Twitter data during natural disasters. First Monday 17(4), 1–8 (2012)
Bruns, A., Burgess, J., Crawford, K., Shaw, F.: # qldfloods and@ QPSMedia: Crisis communication on Twitter in the 2011 south east Queensland floods-Research Report, ARC Centre of Excellence for Creative Industries and Innovation, Australia (2012)
Cvetković, V., Dragicević, S.: Spatial and temporal distribution of natural disasters. J. Geogr. Instit. Jovan Cvijic SASA 64(3), 293–309 (2014)
Deen, S.: Pakistan 2010 floods. Policy gaps in disaster preparedness and response. Int. J. Disaster Risk Reduct. 12, 341–349 (2015)
Gruebner, O., Lowe, S.R., Sykora, M., Shankardass, K., Subramanian, S.V., Galea, S.: Spatio-temporal distribution of negative emotions in New York City after a natural disaster as seen in social media. Int. J. Environ. Res. Public Health 15(10), 1–12 (2018)
Guha-Sapir, D., Hargitt, D., and Hoyois, P.: Thirty years of natural disasters 1974-2003: the numbers (2004). Availabe at https://iri.columbia.edu/~blyon/REFERENCES/P18.pdf. Accessed 21 July 2021
Kaigo, M.: Social media usage during disasters and social capital: Twitter and the Great East Japan earthquake. Keio Commun. Rev. 34(1), 19–35 (2012)
Karami, A., Shah, V., Vaezi, R., Bansal, A.: Twitter speaks: a case of national disaster situational awareness. J. Inf. Sci. (2019). https://doi.org/10.1177/0165551519828620
Karim, A., Noy, I.: Poverty and natural disasters—A qualitative survey of the empirical literature. Singap. Econ. Rev. 61(01), 1640001 (2016)
Kersten, J., Klan, F.: What happens where during disasters? A workflow for the multifaceted characterization of crisis events based on Twitter data. J. Conting. Crisis Manag. 28(3), 262–280 (2020)
Marshall, M.I., Niehm, L.S., Sydnor, S.B., Schrank, H.L.: Predicting small business demise after a natural disaster: an analysis of pre-existing conditions. Nat. Hazards 79(1), 331–354 (2015)
Morgan, G., Smircich, L.: The case for qualitative research. Acad. Manag. Rev. 5(4), 491–500 (1980)
Oh, O., Kwon, K.H., Rao, H.R.: An exploration of social media in extreme events: rumor theory and Twitter during the Haiti earthquake 2010. Icis 231, 7332–7336 (2010)
Ostadtaghizadeh, A., Ardalan, A., Paton, D., Khankeh, H., Jabbari, H.: Community disaster resilience: a qualitative study on Iranian concepts and indicators. Nat. Hazards 83(3), 1843–1861 (2016)
Pourebrahim, N., Sultana, S., Edwards, J., Gochanour, A., Mohanty, S.: Understanding communication dynamics on Twitter during natural disasters: a case study of Hurricane Sandy. Int. J. disaster Risk Reduct. 37, 101176 (2019)
Reyes-Menendez, A., Saura, J.R., Alvarez-Alonso, C.: Understanding #WorldEnvironmentDay user opinions in Twitter: a topic-based sentiment analysis approach. Int. J. Environ. Res. Public Health 15(11), 2537 (2018)
Rudra, K., Ganguly, N., Goyal, P., Ghosh, S.: Extracting and summarizing situational information from the twitter social media during disasters. ACM Trans. Web 12(3), 1–35 (2018)
Sawada, Y., Takasaki, Y.: Natural disaster, poverty, and development: an introduction. World Dev. 94, 2–15 (2017)
Shaw, F., Burgess, J., Crawford, K., Bruns, A.: Sharing news, making sense, saying thanks: patterns of talk on Twitter during the Queensland floods. Aust. J. Commun. 40(1), 23–40 (2013)
Skinner, J.: Natural disasters and Twitter: thinking from both sides of the tweet. First Monday (2013). https://doi.org/10.5210/fm.v18i9.4650
Smith, B.G.: Socially distributing public relations: Twitter, Haiti, and interactivity in social media. Public Relat. Rev. 36(4), 329–335 (2010)
Spence, P.R., Lachlan, K.A., Lin, X., del Greco, M.: Variability in Twitter content across the stages of a natural disaster: implications for crisis communication. Commun. Q. 63(2), 171–186 (2015)
Sreenivasan, N. D., Lee, C. S., & Goh, D. H. L. (2011). Tweet me home: exploring information use on Twitter in crisis situations. In International Conference on Online Communities and Social Computing, 120–129.
Statista. (2020a). Annual number of natural disaster events globally from 2000 to 2019 Available at https://www.statista.com/statistics/510959/number-of-natural-disasters-events-globally/ accessed on January 13, 2020
Statista. (2020b). Number of natural disasters worldwide in 2019, by type Available at https://www.statista.com/statistics/269653/natural-disasters-on-the-continents-by-nature-of-the-disaster/ accessed on March 23, 2021
Stowe, K., Anderson, J., Palmer, M., Palen, L., & Anderson, K. M. (2018). Improving classification of twitter behavior during hurricane events. In Proceedings of the sixth international workshop on natural language processing for social media, 67–75.
Takahashi, B., Tandoc, E.C., Jr., Carmichael, C.: Communicating on Twitter during a disaster: an analysis of tweets during Typhoon Haiyan in the Philippines. Comput. Hum. Behav. 50, 392–398 (2015)
The Weather Channel. (2017). Winter storm Jupiter recap: cross-country snow and ice storm. https://weather.com/storms/winter/news/winter-storm-jupiter-west-snow-plains-midwest-northeast-ice. Accessed on March 26, 2021
Toya, H., Skidmore, M.: Economic development and the impacts of natural disasters. Econ. Lett. 94(1), 20–25 (2007)
Vieweg, S., Hughes, A. L., Starbird, K., & Palen, L. (2010). Microblogging during two natural hazards events: what twitter may contribute to situational awareness. In Proceedings of the SIGCHI conference on human factors in computing systems, 1079–1088.
Viswambharan, A.P., Priya, K.R.: Documentary analysis as a qualitative methodology to explore disaster mental health: insights from analysing a documentary on communal riots. Qual. Res. 16(1), 43–59 (2016)
Wang, Q., Taylor, J.E.: Patterns and limitations of urban human mobility resilience under the influence of multiple types of natural disaster. PLoS One (2016). https://doi.org/10.1371/journal.pone.0147299
Wang, Z., Lam, N.S., Obradovich, N., Ye, X.: Are vulnerable communities digitally left behind in social responses to natural disasters? An evidence from Hurricane Sandy with Twitter data. Appl. Geogr. 108, 1–8 (2019)
Weller, K., Bruns, A., Burgess, J., Mahrt, M., Puschmann, C.: Twitter and society. P. Lang, New York (2014)
WHO: Environmental health in emergencies: natural events. World Health Organization, Switzerland (2017)
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Yum, S. Social networks and spatial-temporal analyses for winter storm Jupiter in the US in 2017. Qual Quant 56, 2091–2105 (2022). https://doi.org/10.1007/s11135-021-01210-x
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DOI: https://doi.org/10.1007/s11135-021-01210-x