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The increasing occurrence of natural disasters and widespread use of social media have increased the scholarly interest to examine the role that social media could potentially play in disaster resilience (Wang et al., 2019). Social media data have been used by researchers in different academic fields (Mocanu et al., 2013), including Geography and Geographic Information Science (GIS) (Wang and Ye, 2019). In particular, the availability of geotagged tweets has opened an important frontier for geographic analysis (Thomee et al., 2016; Yuan, & Medel, 2016).
Twitter is one of the most highly used microblogging services, with millions of monthly active users across the world. Microblogging in Twitter is a form of communication initially composed of 140 characters and recently raised to 280 for all users. The number of twitter users has been increasing significantly over the last few years. According to the Twitter First Quarter of 2020 Earnings Report, monetizable daily active users (mDAU) who accessed Twitter daily are 24% higher than the first quarter of 2019 (Twitter, 2020). The mDAU count is 166 million, including 133 million international users and 33 million U.S based users.
Through Twitter, it is possible to obtain information regarding users’ profiles, their situations, feelings, and experiences, as it often provides immediate and on-location updates (Kireyev, Palen & Anderson, 2009). The scale of information and data provided by Twitter is incomparable to the traditional methods where data is collected primarily by surveys making Twitter a fascinating tool of data collection for research. In particular, Twitter has become a powerful data collection tool during natural disasters (Wang and Ye, 2018), helping environmental managers and planners to identify populations at risk and prepare responses (Houston et al., 2015).
When a disaster occurs, time becomes a determinative factor, and being virtually connected on social media can be an immediate communication solution. Twitter has been revealed a vital source for people affected by a natural disaster to collect real-time information, report about their situation, and requesting help (Olteanu, Vieweg, & Castillo, 2015). For example, during Hurricane Irene, Twitter played a critically vital role as a communication channel (Mandel et al., 2012; Takahashi et al., 2015), adding to the value of Twitter data in disaster research (Li et al., 2015). Many people tweeted to provide or obtain information about the ongoing situation in their communities and to communicate with their friends and families during crisis time (Bird, Ling, & Haynes, 2012; Landwehr & Carley, 2014). Coupling of this information and GIS represents a unique opportunity for decision-makers and planners to improve risk identification and emergency responses (Singleton and Arribas-Bel, 2019; Wang and Ye, 2019).
In disaster studies, social media data has been explored through four dimensions of space, time, content, and network (Wang and Ye, 2018). Among these dimensions, space and content have been explored more extensively than other dimensions (Ye and Wei, 2019). A recent review of 94 papers showed that more than half of the examined articles were focused on content analysis and the rest focused respectively on space, time, and then network analysis (Wang and Ye, 2018).