• Title/Summary/Keyword: disaster text notification

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Covid-19 disaster text notificatioin service using location-based (위치기반을 이용한 코로나 재난 문자 알림 서비스)

  • Kim, Ga-eul;Moon, Seon-yun;Lee, Tae-heon;Park, Min-sook
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.05a
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    • pp.395-396
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    • 2021
  • We have changed a lot in our lives because of a disease called Covid-19.One of the biggest changes is to check the "disaster notification character" service spent in the country every time it is sent in real time. By the way, we cannot accept the characters of other regional disasters other than the area where we live. After visiting other areas, when we returned to the area where we relocated, we experienced difficulty in confirming the flow lines because we could not receive the characters of the flow lines of the corona confirmed persons in the visited areas separately. And if you use the broadcast-type broadcast service, you will not receive unnecessary copper wire information, and you will be able to obtain the characters of the disaster only where we visited. We try to provide app services to provide the public with more accurate and reliable information.

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The Detection Model of Disaster Issues based on the Risk Degree of Social Media Contents (소셜미디어 위험도기반 재난이슈 탐지모델)

  • Choi, Seon Hwa
    • Journal of the Korean Society of Safety
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    • v.31 no.6
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    • pp.121-128
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    • 2016
  • Social Media transformed the mass media based information traffic, and it has become a key resource for finding value in enterprises and public institutions. Particularly, in regards to disaster management, the necessity for public participation policy development through the use of social media is emphasized. National Disaster Management Research Institute developed the Social Big Board, which is a system that monitors social Big Data in real time for purposes of implementing social media disaster management. Social Big Board collects a daily average of 36 million tweets in Korean in real time and automatically filters disaster safety related tweets. The filtered tweets are then automatically categorized into 71 disaster safety types. This real time tweet monitoring system provides various information and insights based on the tweets, such as disaster issues, tweet frequency by region, original tweets, etc. The purpose of using this system is to take advantage of the potential benefits of social media in relations to disaster management. It is a first step towards disaster management that communicates with the people that allows us to hear the voice of the people concerning disaster issues and also understand their emotions at the same time. In this paper, Korean language text mining based Social Big Board will be briefly introduced, and disaster issue detection model, which is key algorithms, will be described. Disaster issues are divided into two categories: potential issues, which refers to abnormal signs prior to disaster events, and occurrence issues, which is a notification of disaster events. The detection models of these two categories are defined and the performance of the models are compared and evaluated.