Social media and severe weather: Do tweets provide a valid indicator of public attention to severe weather risk communication?

Weather, Climate, and Society

Volumn 6, Issue 4, 2014, Pages 520-530

  Ripberger, Joseph T ^a   Jenkins Smith, Hank C ^a   Silva, Carol L ^a   Carlson, Deven E ^a   Henderson, Matthew ^a  

^a UNIVERSITY OF OKLAHOMA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMMUNICATION; ENVIRONMENTAL INDICATOR; PUBLIC ATTITUDE; RISK ASSESSMENT; SOCIAL MEDIA; WEATHER; WORLD WIDE WEB;

EID: 84941006067     PISSN: 19488327     EISSN: 19488335     Source Type: Journal    
DOI: 10.1175/WCAS-D-13-00028.1     Document Type: Article

References (27)

1. Aguirre, B. E., 1988: The lack of warnings before the Saragosa tornado. Int. J. Mass Emerg. Disasters, 6, 65-74.
2. Ahlborn, L., J. M. Franc, and D. S. Med, 2012: Tornado hazard communication disparities among Spanish-speaking individuals in an English-speaking community. Prehosp. Disaster Med., 27, 98-102, doi:10.1017/S1049023X12000015.
3. Brooks, H. E., and C. A. Doswell, 2002: Deaths in the 3 May 1999 Oklahoma City tornado from a historical perspective. Wea. Forecasting, 17, 354-361, doi:10.1175/1520-0434(2002)017〈0354:DITMOC〉2.0.CO;2.
4. Cameron, A. C., and P. K. Trivedi, 1990: Regression-based tests for overdispersion in the Poissonmodel. J. Econometrics, 46, 347-364.
5. Chan, E. H., S. Vikram, C. Conrad, and J. S. Brownstein, 2011: Using web search query data to monitor dengue epidemics: A new model for neglected tropical disease surveillance. PLoS Neglected Trop. Dis., 5, e1206, doi:10.1371/journal.pntd.0001206.
6. Chew, C., and G. Eysenbach, 2010: Pandemics in the age of Twitter: Content analysis of tweets during the 2009 H1N1 outbreak. PLoS ONE, 5, e14118, doi:10.1371/journal.pone.0014118.
7. Donner, W. R., H. Rodriguez, and W. Diaz, 2012: Tornado warnings in three southern states: A qualitative analysis of public response patterns. J. Homeland Security Emerg. Manage., 9, doi:10.1515/1547-7355.1955.
8. Doswell, C. A., A. R. Moller, and H. E. Brooks, 1999: Storm spotting and public awareness since the first tornado forecasts of 1948. Wea. Forecasting, 14, 544-557, doi:10.1175/1520-0434(1999)014〈0544:SSAPAS〉2.0.CO;2.
9. Gelman, A., and J. Hill, 2006: Data Analysis Using Regression and Multilevel/Hierarchical Models. Cambridge University Press, 625 pp.
10. Ginsberg, J., M. H. Mohebbi, R. S. Patel, L. Brammer, M. S. Smolinski, and L. Brilliant, 2009: Detecting influenza epidemics using search engine query data. Nature, 457, 1012-1014, doi:10.1038/nature07634.
11. Greene, W. H., 2011: Econometric Analysis. 7th ed. Prentice Hall, 1232 pp.
12. Hansen, L. K., A. Arvidsson, F. A. Nielsen, E. Colleoni, and M. Etter, 2011: Good friends, bad news - Affect and virality in Twitter. Future Info. Technol., 185, 34-43, doi:10.1007/978-3-642-22309-9-5.
13. Hoang, T.-A., E.-P. Lim, P. Achananuparp, J. Jiang, and F. Zhu, 2011: On modeling virality of Twitter content. Digital Libraries: For Cultural Heritage, Knowledge Dissemination, and Future Creation, Springer, 212-221, doi:10.1007/978-3-642-24826-9-27.
14. Hong, L., O. Dan, and B. D. Davison, 2011: Predicting popular messages in twitter. Proc. 20th Int. Conf. on the World Wide Web, Hyderabad, India, Association for Computing Machinery, 57-58, doi:10.1145/1963192.1963222.
15. Joslyn, S., and S. Savelli, 2010: Communicating forecast uncertainty: Public perception of weather forecast uncertainty. Meteor. Appl., 17, 180-195, doi:10.1002/met.190.
16. Lampos, V., and N. Cristianini, 2010: Tracking the flu pandemic by monitoring the social web. Second Int. Workshop on Cognitive Information Processing, Elba, Italy, IEEE, 411-416, doi:10.1109/CIP.2010.5604088.
17. Lindell, M. K., and R. W. Perry, 2012: The ProtectiveActionDecision Model: Theoretical modifications and additional evidence. Risk Anal., 32, 616-632, doi:10.1111/j.1539-6924.2011.01647.x.
18. Morss, R. E., J. L. Demuth, and J. K. Lazo, 2008: Communicating uncertainty in weather forecasts: A survey of the U.S. public. Wea. Forecasting, 23, 974-991, doi:10.1175/2008WAF2007088.1.
19. NOAA/NWS Storm Prediction Center, 2012: United States tornadoes of 2011. [Available online at www.spc.noaa.gov/wcm/2011-NOAA-NWS-tornado-facts.pdf.]
20. Ripberger, J. T., 2011: Capturing curiosity: Using internet search trends to measure public attentiveness. Policy Stud. J., 39, 239-259, 10.1111/j.1541-0072.2011.00406.x.
21. Sakaki, T., M. Okazaki, and Y. Matsuo, 2010: Earthquake shakes Twitter users: Real-time event detection by social sensors. Proc. 19th Int. Conf. on World Wide Web, New York, NY, ACM, 851-860, doi:10.1145/1772690.1772777.
22. Scharkow, M., and J. Vogelgesang, 2011: Measuring the public agenda using search engine queries. Int. J. Public Opin. Res., 23, 104-113, doi:10.1093/ijpor/edq048.
23. Schmidlin, T. W., P. S. King, B. O. Hammer, and Y. Ono, 1998: Risk factors for death in the 22-23 February 1998 Florida tornadoes. Quick Response Rep. 106. [Available online at www.colorado.edu/hazards/research/qr/qr106/qr106.html.]
24. Sorensen, J., 2000: Hazard warning systems: Review of 20 years of progress. Nat. Hazards Rev., 1, 119-125, doi:10.1061/(ASCE)1527-6988(2000)1:2(119).
25. Szomszor, M., P. Kostkova, and E. de Quincey, 2012: #Swineflu: Twitter predicts swine flu outbreak in 2009. Electronic Healthcare, M. Szomszor and P. Kostkova, Eds., Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, Vol. 69, Springer, 18-26, doi:10.1007/978-3-642-23635-8-3.
26. Tumasjan, A., T. O. Sprenger, P. G. Sandner, and I. M. Welpe, 2010: Predicting elections with Twitter: What 140 characters reveal about political sentiment. Proc. Fourth Int. AAAI Conf. on Weblogs and Social Media, Washington, DC, AAAI, 178-185. [Available online at www.aaai.org/ocs/index.php/ICWSM/ICWSM10/paper/viewFile/1441/1852.]
27. Wilson, K., and J. S. Brownstein, 2009: Early detection of disease outbreaks using the internet. Can. Med. Assoc. J., 180, 829, doi:10.1503/cmaj.1090215.