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Detection of Behavioral Facilitation information in Disaster Situation

Published: 22 February 2020 Publication History

Abstract

Disasters of many types have occurred in recent years, such as strong earthquakes, heavy rain, and typhoons. In such disaster situations, people often use social network services (SNS) and exchange information of all types to help each other. Especially, people exchange information using Twitter during disasters. Such tweet messages include much information that promotes people's behaviors. We designate such tweets as behavioral facilitation tweets. When psychologically unstable in the aftermath of a disaster, behavioral facilitation tweets can strongly affect people, irrespective of a message's authenticity. We regard the extraction of the behavioral facilitation tweets automatically as important. In this paper, we propose a method that extracts behavioral facilitation tweets in disaster situations. Specifically, we propose and compare three methods to extract behavioral facilitation tweets in disaster situations: rule-based, support vector machine (SVM) and long short-term memory (LSTM). Furthermore, we conducted experiments to assess the benefits of our proposed method.

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Cited By

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  • (2024)Analysis of the Effect between the Information Type on SNSs and User Attributes during DisasterCompanion Proceedings of the ACM Web Conference 202410.1145/3589335.3652500(1649-1656)Online publication date: 13-May-2024
  • (2022)Methods of Calculating Usefulness Ratings of Behavioral Facilitation Tweets in Disaster SituationsProceedings of the 11th International Symposium on Information and Communication Technology10.1145/3568562.3568651(88-95)Online publication date: 1-Dec-2022
  • (2021)Extraction and Analysis of Regionally Specific Behavioral Facilitation Information in the Event of a Large-scale DisasterIEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology10.1145/3486622.3493991(538-543)Online publication date: 14-Dec-2021
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        cover image ACM Other conferences
        iiWAS2019: Proceedings of the 21st International Conference on Information Integration and Web-based Applications & Services
        December 2019
        709 pages
        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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        • JKU: Johannes Kepler Universität Linz
        • @WAS: International Organization of Information Integration and Web-based Applications and Services

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        Published: 22 February 2020

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        Author Tags

        1. Disaster
        2. LSTM
        3. Twitter
        4. behavioral facilitation

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        View all
        • (2024)Analysis of the Effect between the Information Type on SNSs and User Attributes during DisasterCompanion Proceedings of the ACM Web Conference 202410.1145/3589335.3652500(1649-1656)Online publication date: 13-May-2024
        • (2022)Methods of Calculating Usefulness Ratings of Behavioral Facilitation Tweets in Disaster SituationsProceedings of the 11th International Symposium on Information and Communication Technology10.1145/3568562.3568651(88-95)Online publication date: 1-Dec-2022
        • (2021)Extraction and Analysis of Regionally Specific Behavioral Facilitation Information in the Event of a Large-scale DisasterIEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology10.1145/3486622.3493991(538-543)Online publication date: 14-Dec-2021
        • (2021)Analysis of Behavioral Facilitation Tweets for Large-Scale Natural Disasters Dataset Using Machine LearningDatabase and Expert Systems Applications10.1007/978-3-030-86475-0_16(161-169)Online publication date: 1-Sep-2021
        • (2020)ANALYSIS OF FACTORS CAUSING DAY ZERO AND PROBLEMS IN WATER GOVERNANCE USING SNS DATA IN CHENNAI, INDIA.インド・チェンナイにおけるDay Zeroの発生要因とSNSデータによる水ガバナンスの課題解析Journal of Japan Society of Civil Engineers, Ser. G (Environmental Research)10.2208/jscejer.76.7_III_5376:7(III_53-III_63)Online publication date: 2020

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