Twitter Data Mining for Situational Awareness

Twitter Data Mining for Situational Awareness

Marco Vernier (University of Udine, Italy), Manuela Farinosi (University of Udine, Italy) and Gian Luca Foresti (Department of Mathematics and Computer Science, University of Udine, Italy)
DOI: 10.4018/978-1-5225-7598-6.ch050

Abstract

The most recent catastrophic events, from the 2010 Haiti earthquake to the devastating 2013 Colorado floods, have shown a strong adoption of social media platforms by ordinary people. The data and metadata produced by the users during and after the extraordinary situations could have enormous potentialities if integrated with the traditional systems for emergency management and used for hyperlocal situational awareness. The great majority of the current literature is focused on Twitter for several reasons strictly linked to the architectures and practices of use of the platform itself. It is possible to classify the existing systems based on the analysis of Twitter data at least in three different categories: 1) semantic systems, 2) metadata systems, and 3) smart self-learning systems. In this chapter, a review of the most significant and important tools used to analyze Twitter data will be presented and an innovative and smart solution will be proposed for future development.
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Background

Social Media Use in Extra-Ordinary Contexts

Social media platforms are built from the beginning to be used socially, and oriented around collaboration and sharing. These potentialities are emphasized in extra-ordinary contexts, when ordinary people adopt these tools to provide or search for first-hand and real-time information regarding a certain event (i.e. an earthquake, flood, etc.) (Lindsay, 2011; Taylor et al., 2012). The most recent catastrophic events, from the 2010 Haiti earthquake to the devastating 2013 Colorado floods, in fact, have shown that these platforms have been strongly used both during and after disasters (Figure 1), allowing a real-time dissemination of information to the wider public, an effective situational awareness, and an up-to-date picture of what is happening on the ground (i.e. Farinosi & Micalizzi, 2013; White et al., 2014).

According to Kotsiopoulos (2014), in extra-ordinary situations, social media enable citizens to play at least three roles: 1) first responders/volunteers; 2) citizen journalists/reporters; and 3) social activists. Oftentimes citizens on the scene experience the event first-hand and are able to provide updates more quickly than disaster response organizations and traditional news media (Sweetser & Metzgar, 2007; Procopio & Procopio, 2007; Farinosi & Micalizzi, 2013).

Given the increasing availability of data and meta-data produced and/or distributed on these online platforms, it is pivotal to understand how they should be used and integrated with traditional systems for situational awareness, supporting in this way the work of Civil Protection, Red Cross, Fire Department, and other agencies.

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