An English-Japanese Twitter-Based Analysis of Disaster Sentiment during Typhoons and Earthquakes

Bernadette Joy Detera, Akira Kodaka, Naohiko Kohtake, Akihiko Nishino, Kaya Onda

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Having proper situational awareness during disaster situations is crucial in planning and mitigation. Knowing people's perception, needs and behavior during disasters is critical in developing the right management strategies. However, cities with multilingual and diverse international populations may react differently to disasters and gaps still exist in understanding this issue. Microblogging with social media has become a prevalent tool during emergencies and disasters. In this paper, we present a method in analyzing the sentiment of both the local residents and foreigners in Tokyo during case studies of earthquake and typhoon. Through the use of Twitter data, we retrieve individual tweets specifically on the onset of the disaster both in Japanese and English. After preprocessing, we develop Machine Learning algorithms using Support Vector Machine and XGBoost to classify tweet sentiment. The sentiment analysis models obtain fair accuracy and could be scaled and applied to sentiment classification of tweets during other types of natural disasters. Moreover, since our model is trained specifically on disaster tweets, it could yield a more accurate and contextual result when applied to future disasters. Furthermore, we analyzed information through Word Cloud, keyword analysis and time series analysis of sentiment polarity. We deduce that Japanese show a more positive sentiment than foreigners at times of disaster. Additionally, we observe that negative sentiment of both groups is lower for typhoons than earthquakes overall. Lastly, using this methodology could provide insights specific to typhoon and earthquake contexts to elicit requirements for disaster information or warning systems catered towards foreigners in the area which could be used in disaster management.

Original languageEnglish
Title of host publicationISSE 2021 - 7th IEEE International Symposium on Systems Engineering, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665431682
DOIs
Publication statusPublished - 2021 Sep 13
Event7th IEEE International Symposium on Systems Engineering, ISSE 2021 - Vienna, Austria
Duration: 2021 Sep 132021 Sep 15

Publication series

NameISSE 2021 - 7th IEEE International Symposium on Systems Engineering, Proceedings

Conference

Conference7th IEEE International Symposium on Systems Engineering, ISSE 2021
Country/TerritoryAustria
CityVienna
Period21/9/1321/9/15

Keywords

  • disasters
  • English
  • Japanese
  • Sentiment Analysis
  • Twitter

ASJC Scopus subject areas

  • Computer Science Applications
  • Hardware and Architecture
  • Energy Engineering and Power Technology
  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Computer Networks and Communications

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