# Use of Social Media Data in Disaster Management: A Survey
###### Abstract  
Social media has played a significant role in disaster management, as it enables the general public to contribute to the monitoring of disasters by reporting incidents related to disaster events. However, the vast volume and wide variety of generated social media data create an obstacle in disaster management by limiting the availability of actionable information from social media. Several approaches have therefore been proposed in the literature to cope with the challenges of social media data for disaster management. To the best of our knowledge, there is no published literature on social media data management and analysis that identifies the research problems and provides a research taxonomy for the classification of the common research issues. In this paper, we provide a survey of how social media data contribute to disaster management and the methodologies for social media data management and analysis in disaster management. This survey includes the methodologies for social media data classification and event detection as well as spatial and temporal information extraction. Furthermore, a taxonomy of the research dimensions of social media data management and analysis for disaster management is also proposed, which is then applied to a survey of existing literature and to discuss the core advantages and disadvantages of the various methodologies. social media; social media data; disaster management; survey +
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of the world's population [5]. Facebook had over 2.6 billion monthly active users (MAUs) and 1.73 billion daily active users as of March 31 2020. Twitter had 330 million MAUs and 145 million daily active users [6] in 2019. A total of 500 million tweets are sent by Twitter users every day, equivalent to 5787 tweets per second [7]. Moreover, there were 1 billion MAUs on Instagram as of June 2018, and 500 million daily active users updated their stories. The large number of posts generated by these active users exemplifies the variety of dimensions of social media data. For instance, Twitter data are comprised of several types of information, including account IDs, timestamps, user tweets (e.g., texts, images, videos), coordinates, retweets, and so forth. The volume, velocity, and variety of data thus make it increasingly difficult for disaster managers to extract relevant and timely information from such data. A comprehensive taxonomical framework is presented in this article to effectively explore, assess, contrast, and compare existing approaches that use social media data for disaster management. Previous surveys in this subject area have mostly focused on specific aspects; hence, they appear to be narrow and fragmented. Topics include: (i) digital volunteerism [8]; (ii) disaster management lifecycle [9], including Warning, Impact, Response, and Relief; and (iii) disaster response ([10,11]). They consider aspects such as space, time, content, and network reach. Although the above-mentioned papers classified the literature based on taxonomies that covered aspects related to the effects of emergency occurrences on social media, social media data gathering and processing, and social media's effect on post-disaster management, they are limited in scope, with only a \"broad\" significance. In contrast, we present a holistic and comprehensive taxonomical framework. We propose a taxonomy that is much more exhaustive, with additional (sub-)dimensions that contribute to an \"in-depth\" understanding of end-to-end challenges (e.g., data source, application, methodology, information dimension, and language) related to managing social media data for detecting, predicting, and responding to natural disasters. To date, this level of investigation has received little attention, and this article aims to alleviate this gap.