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Domain-Independent Detection of Emergency Situations Based on Social Activity Related to Geolocations

Published: 15 May 2018 Publication History

Abstract

In general, existing methods for automatically detecting emergency situations using Twitter rely on features based on domain-specific keywords found in messages. This type of keyword-based methods usually require training on domain-specific labeled data, using multiple languages, and for different types of events (e.g., earthquakes, floods, wildfires, etc.). In addition to being costly, these approaches may fail to detect previously unexpected situations, such as uncommon catastrophes or terrorist attacks. However, collective mentions of certain keywords are not the only type of self-organizing phenomena that may arise in social media when a real-world extreme situation occurs. Just as nearby physical sensors become activated when stimulated, localized citizen sensors (i.e., users) will also react in a similar manner. To leverage this information, we propose to use self-organized activity related to geolocations to identify emergency situations. We propose to detect such events by tracking the frequencies, and probability distributions of the interarrival time of the messages related to specific locations. Using an off-the-shelf classifier that is independent of domain-specific features, we study and describe emergency situations based solely on location-based features in messages. Our findings indicate that anomalies in location-related social media user activity indeed provide information for automatically detecting emergency situations independent of their domain.

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  • (2021)Crisis communicationProceedings of the 36th Annual ACM Symposium on Applied Computing10.1145/3412841.3442044(1711-1720)Online publication date: 22-Mar-2021
  • (2020)Minding the AI gap in LATAMCommunications of the ACM10.1145/341696963:11(61-63)Online publication date: 22-Oct-2020
  • (2019)A Domain-Independent and Multilingual Approach for Crisis Event Detection and UnderstandingProceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3331184.3331425(1457-1457)Online publication date: 18-Jul-2019
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      cover image ACM Conferences
      WebSci '18: Proceedings of the 10th ACM Conference on Web Science
      May 2018
      399 pages
      ISBN:9781450355636
      DOI:10.1145/3201064
      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 the author(s) 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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      Publication History

      Published: 15 May 2018

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      Author Tags

      1. citizen sensors
      2. emergency situations
      3. social media

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      WebSci '18: 10th ACM Conference on Web Science
      May 27 - 30, 2018
      Amsterdam, Netherlands

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      WebSci '18 Paper Acceptance Rate 30 of 113 submissions, 27%;
      Overall Acceptance Rate 245 of 933 submissions, 26%

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      Cited By

      View all
      • (2021)Crisis communicationProceedings of the 36th Annual ACM Symposium on Applied Computing10.1145/3412841.3442044(1711-1720)Online publication date: 22-Mar-2021
      • (2020)Minding the AI gap in LATAMCommunications of the ACM10.1145/341696963:11(61-63)Online publication date: 22-Oct-2020
      • (2019)A Domain-Independent and Multilingual Approach for Crisis Event Detection and UnderstandingProceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3331184.3331425(1457-1457)Online publication date: 18-Jul-2019
      • (2019)A Lightweight Representation of News Events on Social MediaProceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3331184.3331300(1049-1052)Online publication date: 18-Jul-2019
      • (2019)A global database of historic and real-time flood events based on social mediaScientific Data10.1038/s41597-019-0326-96:1Online publication date: 9-Dec-2019

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