Preprints
https://doi.org/10.5194/egusphere-2024-1536
https://doi.org/10.5194/egusphere-2024-1536
17 Jun 2024
 | 17 Jun 2024
Status: this preprint is open for discussion.

Review Article: Leveraging Social Media for Managing Natural Hazard Disasters: A Critical Review of Data Collection Strategies and Actionable Insights

Lakshmi S. Gopal, Rekha Prabha, Hemalatha Thirugnanam, Maneesha Vinodini Ramesh, and Bruce D. Malamud

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.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Lakshmi S. Gopal, Rekha Prabha, Hemalatha Thirugnanam, Maneesha Vinodini Ramesh, and Bruce D. Malamud

Status: open (until 22 Aug 2024)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
Lakshmi S. Gopal, Rekha Prabha, Hemalatha Thirugnanam, Maneesha Vinodini Ramesh, and Bruce D. Malamud

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

Lakshmi S. Gopal, Rekha Prabha, Hemalatha Thirugnanam, Maneesha Vinodini Ramesh, and Bruce D. Malamud

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Short summary
We critically reviewed 250 articles from 2010 to 2023, analysed how social media is used to manage disasters, and developed the Social Media Literature Database. We summarise the methods used for data collection and filtering. Key findings include the widespread use of the latest technologies to handle data, proficiency in spatiotemporal analysis, and gaps in community interaction and resource identification. We also propose best practices for using social media to enhance disaster management.