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A Linguistically-driven Approach to Cross-Event Damage Assessment of Natural Disasters from Social Media Messages

Published: 18 May 2015 Publication History

Abstract

This work focuses on the analysis of Italian social media messages for disaster management and aims at the detection of messages carrying critical information for the damage assessment task. A main novelty of this study consists in the focus on out-domain and cross-event damage detection, and on the investigation of the most relevant tweet-derived features for these tasks. We devised different experiments by resorting to a wide set of linguistic features qualifying the lexical and grammatical structure of a text as well as ad-hoc features specifically implemented for this task. We investigated the most effective features that allow to achieve the best results. A further result of this study is the construction of the first manually annotated Italian corpus of social media messages for damage assessment.

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  1. A Linguistically-driven Approach to Cross-Event Damage Assessment of Natural Disasters from Social Media Messages

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      cover image ACM Other conferences
      WWW '15 Companion: Proceedings of the 24th International Conference on World Wide Web
      May 2015
      1602 pages
      ISBN:9781450334730
      DOI:10.1145/2740908

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      • IW3C2: International World Wide Web Conference Committee

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      Association for Computing Machinery

      New York, NY, United States

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      Published: 18 May 2015

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      Author Tags

      1. crisis informatics
      2. damage assessment
      3. emergency management
      4. feature selection
      5. social media mining
      6. social sensing

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      Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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      • (2024)Digital Post-Disaster Risk Management Twinning: A Review and Improved Conceptual FrameworkInternational Journal of Disaster Risk Reduction10.1016/j.ijdrr.2024.104629(104629)Online publication date: Jun-2024
      • (2024)A Comprehensive Study on Disaster Tweet Classification on Social Media InformationSoft Computing and Signal Processing10.1007/978-981-99-8628-6_43(507-516)Online publication date: 16-Apr-2024
      • (2023)Cyber-Physical-Social Awareness Platform for Comprehensive Situation AwarenessSensors10.3390/s2302082223:2(822)Online publication date: 10-Jan-2023
      • (2023)Simplistic Collection and Labeling Practices Limit the Utility of Benchmark Datasets for Twitter Bot DetectionProceedings of the ACM Web Conference 202310.1145/3543507.3583214(3660-3669)Online publication date: 30-Apr-2023
      • (2023)Application of Social Sensors in Natural Disasters Emergency Management: A ReviewIEEE Transactions on Computational Social Systems10.1109/TCSS.2022.321155210:6(3143-3158)Online publication date: Dec-2023
      • (2022)GNoM: Graph Neural Network Enhanced Language Models for Disaster Related Multilingual Text ClassificationProceedings of the 14th ACM Web Science Conference 202210.1145/3501247.3531561(55-65)Online publication date: 26-Jun-2022
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      • (2022)Early detection of emergency events from social media: a new text clustering approachNatural Hazards10.1007/s11069-021-05081-1111:1(851-875)Online publication date: 22-Jan-2022
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