Best Papers
 Evaluating Urgency Levels of Emergency Alerts through Sentiment Analysis 


Vol. 49,  No. 2, pp. 226-236, Feb.  2024
10.7840/kics.2024.49.2.226


PDF Full-Text
  Abstract

Emergency alerts are crucial means for promptly and accurately conveying disaster information in urgent situations. However, as the type and frequency of emergency alerts delivered to the public increase, there has been a rise in public fatigue and a decline in trust. To evaluate the appropriateness of the emergency alert service, this study proposes models that evaluate urgency levels for emergency alerts based on sentiment analysis. The models are developed using four representative natural language processing algorithms. Furthermore, criteria and methodology for evaluating urgency levels are presented. In the experimental results, among the four algorithms, the urgency level evaluation model based on the Bidirectional Encoder Representations from Transformers algorithm showed the best learning performance with an accuracy of 98%. And through the four learned algorithm-based urgency level evaluation models, the urgency of the emergency alerts issued in 2022 was classified and evaluated.

  Statistics
Cumulative Counts from November, 2022
Multiple requests among the same browser session are counted as one view. If you mouse over a chart, the values of data points will be shown.


  Related Articles
  Cite this article

[IEEE Style]

S. Ju, H. Kang, S. Oh, "Evaluating Urgency Levels of Emergency Alerts through Sentiment Analysis," The Journal of Korean Institute of Communications and Information Sciences, vol. 49, no. 2, pp. 226-236, 2024. DOI: 10.7840/kics.2024.49.2.226.

[ACM Style]

Sang-Lim Ju, Hyunjoo Kang, and Seung-Hee Oh. 2024. Evaluating Urgency Levels of Emergency Alerts through Sentiment Analysis. The Journal of Korean Institute of Communications and Information Sciences, 49, 2, (2024), 226-236. DOI: 10.7840/kics.2024.49.2.226.

[KICS Style]

Sang-Lim Ju, Hyunjoo Kang, Seung-Hee Oh, "Evaluating Urgency Levels of Emergency Alerts through Sentiment Analysis," The Journal of Korean Institute of Communications and Information Sciences, vol. 49, no. 2, pp. 226-236, 2. 2024. (https://doi.org/10.7840/kics.2024.49.2.226)
Vol. 49, No. 2 Index

Search
(IN TITLE, AUTHOR, ABSTRACT,KEYWORDS)

Advanced Search ▼

POPULAR KEYWORDS
(TOP 10 KEYWORDS)

Recent Publications
(LAST 3 YEARS)






pISSN : 1226 - 4717
eISSN : 2287 - 3880