In this chapter, the author describes the cases for the study’s analyses, research questions, and methodology to achieve this study’s goal that is to show the potential usefulness of social media data for detecting socio-economic recovery. First, in Sect. 3.1, the author introduces two large-scale disaster cases for the analysis of this study: the Great East Japan Earthquake and Tsunami of 2011 and Hurricane Sandy in 2012. In Sect. 3.2, the research questions and the research flowchart are described. Next, in Sect. 3.3, the data and the methodology regarding socio-economic recovery activities are provided. Lastly, in Sect. 3.4, the author explains the data and the methodology for applying the “people as sensors” approach. In Sect. 3.5, the author briefly summarizes this chapter.
- Asahi Shimbun. (2011, April 16th). Cyukosya Jyuyo ga Kyuzo [Increasing demand for used cars]., p. 8. (in Japanese).Google Scholar
- Asahi Shimbun. (2011, May 30th). Hisaichi no takadai tika jyosyo [land price increase in disaster-impacted areas]., p. 39. (in Japanese).Google Scholar
- Barr, J., Cohen, J. P., & Kim, E. (2017). Storm surges, informational shocks, and the price of Urban Real Estate: An application to the case of Hurricane Sandy. Rutgers University, Newark 2017-002, Department of Economics, Rutgers University, Newark. https://sasn.rutgers.edu/academics-admissions/academic-departments/economics/faculty-publications, working paper.
- Beigi, G, Hu, X., Maciejewski, R., & Liu, H. (2016). An overview of sentiment analysis in social media and its applications in disaster relief (pp. 313–340). In: Pedrycz W., Chen SM. (eds) Sentiment Analysis and Ontology Engineering. Studies in Computational Intelligence, 639. Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-30319-2_13.CrossRefGoogle Scholar
- Blake, E. S., Kimberlain, T. B., Berg, R. J., Cangialosi, J. P., & Beven Ii, J. L. (2013). Tropical cyclone report: Hurricane sandy (pp 1–10). https://www.nhc.noaa.gov/data/tcr/AL182012_Sandy.pdf.
- Bloomberg, M. (2013). A stronger, more resilient. New York. https://www1.nyc.gov/site/sirr/report/report.page.
- Chatfield, A. T., Scholl, H. J., & Brajawidagda, U. (2014). #Sandy tweets: Citizens’ Co-Production of time-critical information during an unfolding catastrophe. In: Proceedings of 2014 47th Hawaii International Conference on System Sciences (pp. 1947–1957). IEEE. https://doi.org/10.1109/HICSS.2014.247.
- Kearns, J., Pak, S., & Buhayar, N. (2012). Now get ready for a huge economic boost from hurricane sandy. https://www.businessinsider.com/economic-boost-from-hurricane-sandy-2012-11
- Lu, X., & Brelsford, C. (2014). Network structure and community evolution on twitter: Human behavior change in response to the 2011. Scientific Reports, 4(6773), 1–11. https://doi.org/10.1038/srep06773.
- Mainichi Shimbun. (2011, May 11th). Higashinihon daishinsai: Hisaichi de cyukosya koto [the great east japan earthquake and tsunami: The prices of used-car increased in the damaged areas]., p. 26 (in Japanese).Google Scholar
- Mainichi Shimbun. (2012, September 20th). Kizyun chika [standard price of lands]., p. 27 (in Japanese).Google Scholar
- Nakabayashi, I. (2016). Saigai fukkou kenkyu no igi to tembou [meanings and prospects of disaster recovery research]. Fukkou, 7(3), 34–41. (in Japanese).Google Scholar
- NBC. (2014). Anniversary of Superstorm Sandy, Snowstorm. https://www.nbcconnecticut.com/news/local/Anniversary-of-October-Snowstorm-Super-Storm-Sandy-280815872.html.
- Nikkei Sangyo Shimbun. (2011, May 17th). Cyukosya toroku hisaichi de kyuzou [register of used cars increased in the disaster-striken area]., p. 3. (in Japanese).Google Scholar
- Nikkei Shimbun. (2012a, March 11th). Higashinihon daishinsai ichi nen fukkou gan nen youyaku miyagi ken chiji murai yoshihiro shi [one year after the great east japan earth- quake and tsunami: The first year of recovery: Mayor of miyagi prefecture, yasuhiro murai]., p.16. (in Japanese).Google Scholar
- Prieto, M., Caemmerer, B., & Baltas, G. (2015). Using a hedonic price model to test prospect theory assertions: The asymmetrical and nonlinear effect of reliability on used car prices. Journal of Retailing and Consumer Services, 22(2015), 206–212. https://doi.org/10.1016/j.jretconser.2014.08.013.CrossRefGoogle Scholar
- Racioppi, D. (2014). New homes in demand on Long Beach Island. https://www.app.com/story/news/local/ocean-county/2014/10/03/lbi-building-boom-sandy/16654755/
- Rubin, C. B. (1985). The community recovery process in the united states after a major natural disaster. International Journal of Mass Emergencies and Disasters, 3(2), 9–28.Google Scholar
- Sumiyoshi, Y., Inagaki, K., & Sadohara, S. (2018). Shizen saigai ga fudousan ni ataeru eikyou bunseki [analysis of how a natural disaster influence property price]. In Proceedings of Architectural Institute of Japan Annual Meeting (pp. 885–886), (in Japanese).Google Scholar
- Tatsuki, S., & Hayashi, H. (2002). Seven critical element model of life recovery: General linear model analyses of the 2001 Kobe panel survey data. In Proceedings of 2nd Workshop for Comparative Study on Urban Earthquake Disaster Management.Google Scholar
- The Cabinet Office. (2012). Annual economic finance report. http://www5.cao.go.jp/j-j/wp/wp-je12/index.html, (in Japanese).
- The City of New York. (2013). Sandy and its impacts. http://www.nyc.gov/html/sirr/downloads/pdf/final_report/Ch_1_SandyImpacts_FINAL_singles.pdf.
- The Tohoku Finance Bureaus. (2017). Zaimu Kyoku Cyosa niyoru Kakuchiiki no Syouhi ni Kansuru Tokutyouteki na Doukou [Reports on Regional trends of consumption]. http://www.mof.go.jp/about_mof/zaimu/kannai/201604/shouhinodoukou084.pdf, (in Japanese).
- Yasuda, S., Yukutake, N., & Naoi, M. (2018). The impact of earthquake risk on housing market before and after the Great East Japan earthquake. Keio-IES discussion paper series. https://ideas.repec.org/p/keo/dpaper/2018-011.html, (in Japanese).