the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Review Article: Leveraging Social Media for Managing Natural Hazard Disasters: A Critical Review of Data Collection Strategies and Actionable Insights
Abstract. This paper critically reviews 250 articles from 2010 to September 2023, analyzing how social media data is utilized in disaster management, addressing challenges in relevance filtering and noise reduction to extract actionable disaster information and enhance decision-making efficiency. The results of our critical analysis are given in a Social Media Literature Database where we categorize each article's information into 7 main categories and 27 subcategories, covering article details, case study regions, disaster events, social media data specifics, data collection and analysis methods, and evaluation methodologies. To assess the effectiveness of social media in providing actionable disaster information, we further classify the articles into 9 categories, covering public discourse analysis, temporal and spatial insights, relevance filtering methods, community/stakeholder collaborations, disaster trends, and resource identification. We also illuminate historical disaster events within the review period and discuss the results through graphical visualizations. Our findings show that natural language processing methods, particularly content analysis, were commonly utilized in the literature, and contribute significantly to basic data filtering by removing noise. Commonly used advanced robust analysis machine learning methods included Support Vector Machines, Naive Bayes, and Neural Networks. We found that proficiency in temporal and spatial analysis of social media data is widespread among the studies, with varying success in implementing effective relevance filtering. Our actionable information categorization revealed a need for further exploration into community interactions and resource identification using social media data during and after disasters. Based on the literature study and our own experience on the subject, we propose six best practices for social media usage in disaster situations for the community and five best practices for researchers to enhance disaster management strategies.
- Preprint
(3331 KB) - Metadata XML
- BibTeX
- EndNote
Status: open (until 30 Nov 2024)
-
RC1: 'Comment on egusphere-2024-1536', Anonymous Referee #1, 10 Jul 2024
reply
Please see my comments in the attached file
-
AC1: 'Reply on RC1', Lakshmi S Gopal, 31 Jul 2024
reply
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1536/egusphere-2024-1536-AC1-supplement.pdf
-
RC2: 'Reply on AC1', Anonymous Referee #1, 05 Aug 2024
reply
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1536/egusphere-2024-1536-RC2-supplement.pdf
-
RC2: 'Reply on AC1', Anonymous Referee #1, 05 Aug 2024
reply
-
AC1: 'Reply on RC1', Lakshmi S Gopal, 31 Jul 2024
reply
Data sets
Social Media Literature Database Lakshmi S. Gopal, Rekha Prabha, Hemalatha Thirugnanam, Maneesha Vinodini Ramesh, and Bruce D. Malamud https://doi.org/10.5281/zenodo.10803017
Viewed
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
391 | 179 | 68 | 638 | 10 | 11 |
- HTML: 391
- PDF: 179
- XML: 68
- Total: 638
- BibTeX: 10
- EndNote: 11
Viewed (geographical distribution)
Country | # | Views | % |
---|
Total: | 0 |
HTML: | 0 |
PDF: | 0 |
XML: | 0 |
- 1