Social Media Data Analytics to Enhance Sustainable Communications between Public Users and Providers in Weather Forecast Service Industry

Ki-Kwang Lee and In-Gyum Kim
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Ki-Kwang Lee: School of Business Administration, Dankook University, Yongin-si, Gyeonggi-do 16890, Korea
In-Gyum Kim: Planning and Finance Division, National Institute of Meteorological Sciences, Seogwipo-si, Jeju-do 63568, Korea

Sustainability, 2020, vol. 12, issue 20, 1-13

Abstract: The weather forecast service industry needs to understand customers’ opinions of the weather forecast to enhance sustainable communication between forecast providers and recipients particularly influenced by inherent uncertainty in the forecast itself and cultural factors. This study aims to investigate the potential for using social media data to analyze users’ opinions of the wrong weather forecast. Twitter data from Korea in 2014 are analyzed using textual analysis and association rule mining to extract meaningful emotions or behaviors from weather forecast users. The results of textual analysis show that the frequency of negative opinions is considerably high compared to positive opinions. More than half of the tweets mention precipitation forecasts among the meteorological phenomena, implying that most Koreans are sensitive to rain events. Moreover, association rules extracted from the negative tweets reveal a pattern of user criticism according to the seasons and types of forecast errors such as a “false alarm” or “miss” error. This study shows that social media data can provide valuable information on the actual opinion of the forecast users in almost real time, enabling the weather forecast providers to communicate effectively with the public.

Keywords: customer opinion; types of forecast errors; text mining; sustainable meteorological service industry (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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