# Use of Social Media Data in Disaster Management: A Survey
## 3 Materials and Methods
### Survey Procedure  
The taxonomy presented in Section 3.1 is defined based on the common research issues mentioned in the selected publications in this survey. Our process for choosing the publications is divided into four main steps: (i) taxonomy and keyword determination, (ii) publication search, (iii) publication review, and (iv) publication selection.  
* Step i. Taxonomy and keyword determination: We created a primary taxonomy and identified keywords based on the application of social media data in disaster management. The taxonomy and keywords were determined based on the requirements of our ongoing Landslip project ([[http://www.landslip.org](http://www.landslip.org)]([http://www.landslip.org](http://www.landslip.org)) (accessed on 17 December 2020)). The keywords were further used in step ii to search for publication candidates. Further, the set of keywords and taxonomy were iteratively refined throughout the process. We also used the keywords provided in the selected papers (in step iv) to identify more keywords and to analyse the critical issues in the selected papers to refine the taxonomy.
* Step ii. Publication search: We searched for publication candidates from several potential repositories based on the set of keywords identified in step i. The main publication repositories and search engine used in this step included IEEE Xplore ([[https://ieeexplore.ieee.org](https://ieeexplore.ieee.org)]([https://ieeexplore.ieee.org](https://ieeexplore.ieee.org)) (accessed on 2 September 2020)), ACM Digital Library ([[https://dl.acm.org](https://dl.acm.org)]([https://dl.acm.org](https://dl.acm.org)) (accessed on 2 September 2020)), SpringerLink ([[https://link.springer.com](https://link.springer.com)]([https://link.springer.com](https://link.springer.com)) (accessed on 2 September 2020)), ScienceDirect [[https://www.sciencedirect.com](https://www.sciencedirect.com)]([https://www.sciencedirect.com](https://www.sciencedirect.com)) (accessed on 2 September 2020)), and Google Scholar ([[https://scholar.google.com](https://scholar.google.com)]([https://scholar.google.com](https://scholar.google.com)) (accessed on 2 September 2020)). In addition, the search results from Google Scholar led to the sources of the publication candidates, which included ResearchGate, JMR, ScienceAdvances, PLOS, MDPI, and Tandfonline. The keywords could be classified into three main classes: Social Media (e.g., Social Media, Social Network, Crowdsourcing, Twitter, Microlbogs), Disaster (e.g., Disaster Management, Emergency Management, Landslide, Earthquake, Flood, Rainfall), and Data Management and Analysis (e.g., Data Analysis, Data Management, Data Mining). The search for publications was based on the combinations of keywords from these classes, which helped to narrow down the search, leading to more focused and relevant results.
* Step iii. Publication review: The search results of publications returned from repositories and search engines were reviewed and selected as candidates based on information provided in the title, keywords, and abstract of the publications and if they were relevant to one of the scopes defined in the taxonomy (Section 3.1). As a result, 200 publications from the repositories and search engines were selected as publication candidates.
* Step iv. Publication selection: We scanned through the contents of the publication candidates and selected the publications for this survey based on their relevance to terms in the taxonomy. For example, Reference [16] was one of the selected papers that provided information relevant to all terms defined in the taxonomy shown in Section 3.1. Accordingly, 40 publications from several repositories and search engines were selected. These are presented in Table 1. Next, we analysed the selected publications to extract more keywords and to update the list of the keywords identified in step i. Furthermore, critical issues mentioned in the selected papers were used to refine and update terms and sub-terms in the taxonomy.