Browse > Article
http://dx.doi.org/10.11627/jkise.2018.41.2.009

Public Satisfaction Analysis of Weather Forecast Service by Using Twitter  

Lee, Ki-Kwang (Department of Business Administration, Dankook University)
Publication Information
Journal of Korean Society of Industrial and Systems Engineering / v.41, no.2, 2018 , pp. 9-15 More about this Journal
Abstract
This study is intended to investigate that it is possible to analyze the public awareness and satisfaction of the weather forecast service provided by the Korea Meteorological Administration (KMA) through social media data as a way to overcome limitations of the questionnaire-based survey in the previous research. Sentiment analysis and association rule mining were used for Twitter data containing opinions about the weather forecast service. As a result of sentiment analysis, the frequency of negative opinions was very high, about 75%, relative to positive opinions because of the nature of public services. The detailed analysis shows that a large portion of users are dissatisfied with precipitation forecast and that it is needed to analyze the two kinds of error types of the precipitation forecast, namely, 'False alarm' and 'Miss' in more detail. Therefore, association rule mining was performed on negative tweets for each of these error types. As a result, it was found that a considerable number of complaints occurred when preventive actions were useless because the forecast predicting rain had a 'False alarm' error. In addition, this study found that people's dissatisfaction increased when they experienced inconveniences due to either unpredictable high winds and heavy rains in summer or severe cold in winter, which were missed by weather forecast. This study suggests that the analysis of social media data can provide detailed information about forecast users' opinion in almost real time, which is impossible through survey or interview.
Keywords
Social Media; Twitter; Sentiment Analysis; Association Rule Mining; Weather Forecast;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 Drobot, S., Anderson, A.R.S., Burghardt, C., and Pisano, P., U.S. Public Preferences for Weather And Road Condition Information, Bulletin of American Meteorological Society, 2014, Vol. 95, pp. 849-859.   DOI
2 Emanuel, K., Will Global Warming Make Hurricane Forecasting More Difficult?, Bulletin of American Meteorological Society, 2017, Vol. 98, pp. 495-501.   DOI
3 Gregow, H., Jylha, K., Makela, H.M., Alto, J., Manninen, T., Karlsson, P., Kaiser-Weiss, A.K., Kaspar, F., Poli, P., Tan, D.G.H., Obregon, A., and Su, Z., Worldwide Survey of Awareness And Needs Concerning Reanalyses And Respondents Views on Climate Sservices, Bulletin of American Meteorological Society, 2016, Vol. 97, No. 8, pp. 1461-1473.   DOI
4 Jansen, B.J., Zhang, M., Sobel, K., and Chowdury, A., Twitter Power : Tweets as Electronic Word of Mouth, Journal of American Society of Information Science and Technology, 2009, Vol. 60, No. 11, pp. 2169-2188.   DOI
5 Joslyn, S. and Savelli, S., Communicating Forecast Uncertainty : Public Perception of Weather Forecast Uncertainty, Meteorological Applications, 2010, Vol. 17, No. 2, pp. 180-195.   DOI
6 Kim, I., Kim, J., Kim, B., and Lee, K., The Collective Value of Weather Probabilistic Forecasts According to Public Threshold Distribution Patterns, Meteorological Applications, 2014, Vol. 21, No. 3, pp. 795-802.   DOI
7 Kim, K. and Ku, J., A Study on the Potential and Limitation of Pre-producing Dramas through Social Analysis, Journal of the Korea Academia-Industrial Cooperation Society, 2018, Vol. 19, No. 2, pp. 164-172.   DOI
8 Baghestani, H. and Williams, P., Does Customer Satisfaction Have Directional Predictability for U.S. Discretionary Spending?, Applied Economics, 2017, Vol. 49, No. 54, pp. 5504-5511.   DOI
9 Demuth, J.L., Morss, R.E., Morrow, B.H., and Lazo, J.K., Creation And Communication of Hurricane Risk Information, Bulletin of American Meteorological Society, 2012, Vol. 93, Vol. 8, pp. 1113-1145.
10 KMA, Public satisfaction survey on national weather service in 2016, web.kma.go.kr/notify/information/publication_depart_list.jsp?bid=depart&mode=view&num=246&page=1&field=&text=&schGrp=7.
11 Agarwal, R. and Srikant, R., Fast Algorithms for Mining Association Rules in Large Databases, Proceedings of 20th International Conference on Very Large DataBases, Santiago, Chile, 1994, pp. 487-499.
12 Anderson, E.W., Customer Satisfaction And Word of Mouth, Journal of Service Research, 1998, Vol. 1, No. 1, pp. 5-17.   DOI
13 Lee, K. and Lee, J., The Effect of Meteorological Information on Business Decision-Making with a Value Score Model, Journal of Society of Korea Industrial and Systems Engineering, 2007, Vol. 30, No. 2, pp. 89-98.
14 Morrow, B.H., Lazo, J.K., Rhome, J., and Feyen, J., Improving Storm Surge Risk Communication : Stakeholder Perspectives, Bulletin of American Meteorological Society, 2015, Vol. 96, No. 1, pp. 35-48.   DOI
15 Sherman-Morris, K., Senkbeil, J., and Carver, R., Who's Googling What?, Bulletin of American Meteorological Society, 2011, Vol. 92, No. 8, pp. 975-985.   DOI
16 Morss, R.E., Lazo, J.K., and Demuth, J.L., Examining the Use of Weather Forecasts in Decision Scenarios : Results from a US Survey with Implications for Uncertainty Communication, Meteorological Applications, 2010, Vol. 17, No. 2, pp. 149-162.   DOI
17 Ramos, M.-H., Mathevet, T., Thielen, J., and Pappenberger, F., Communicating Uncertainty in Hydro-meteorological Forecasts : Mission Impossible?, Meteorological Applications, 2010, Vol. 17, No. 2, pp. 223-235.   DOI
18 Schacter, D.L., Memory distortion, Harvard University Press, 1995, pp. 1-46.
19 Silver, A. and Conrad, C., Public Perception of And Response to Severe Weather Warnings in Nova Scotia, Canada, Meteorological Applications, 2010, Vol. 17, No. 2, pp. 173-179.   DOI
20 Smith, A.B. and Katz, R.W., US Billion-dollar Weather And Climate Disasters : Data Sources, Trends, Accuracy And Biases, Nature Hazards, 2013, Vol. 67, No. 2, pp. 387-410.   DOI
21 Walle, S.V.D. and Ryzin, G.G.V., The Order of Questions in a Survey on Citizen Satisfaction with Public Services : Lessons from a Split-ballot Experiment, Public Administrations, 2011, Vol. 89, No. 4, pp. 1436-1450.   DOI
22 Zabini, F., Grasso, V., Magno, R., Meneguzzo, F., and Gozzini, B., Communication And Interpretation of Regional Weather Forecasts : a Survey of the Italian Public, Meteorological Applications, 2015, Vol. 22, No. 3, pp. 495-504.   DOI
23 Zaltman, G., Rethinking Market Research : Putting People Back in, Journal of Marketing Research, 1997, Vol. 34, No. 4, pp. 424-437.   DOI
24 Zhao, Y., R and data mining-examples and case studies, Elsevier, 2013, pp. 89-92.