Geovisual analytics and interactive machine learning for situational awareness

M Karimzadeh, LS Snyder, DS Ebert - arXiv preprint arXiv:1910.05441, 2019 - arxiv.org
arXiv preprint arXiv:1910.05441, 2019arxiv.org
The first responder community has traditionally relied on calls from the public, officially-
provided geographic information and maps for coordinating actions on the ground. The
ubiquity of social media platforms created an opportunity for near real-time sensing of the
situation (eg unfolding weather events or crises) through volunteered geographic
information. In this article, we provide an overview of the design process and features of the
Social Media Analytics Reporting Toolkit (SMART), a visual analytics platform developed at …
The first responder community has traditionally relied on calls from the public, officially-provided geographic information and maps for coordinating actions on the ground. The ubiquity of social media platforms created an opportunity for near real-time sensing of the situation (e.g. unfolding weather events or crises) through volunteered geographic information. In this article, we provide an overview of the design process and features of the Social Media Analytics Reporting Toolkit (SMART), a visual analytics platform developed at Purdue University for providing first responders with real-time situational awareness. We attribute its successful adoption by many first responders to its user-centered design, interactive (geo)visualizations and interactive machine learning, giving users control over analysis.
arxiv.org
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