Journal cover Journal topic
Proceedings of the ICA
Journal topic
Articles | Volume 1
https://doi.org/10.5194/ica-proc-1-101-2018
https://doi.org/10.5194/ica-proc-1-101-2018
16 May 2018
 | 16 May 2018

A Framework for Enhancing Real-time Social Media Data to Improve Disaster Management Process

Syed Attique Shah, Dursun Zafer Şeker, and Hande Demirel

Keywords: Crowd Sourcing, Disaster Management, Design Science, Social Media, Real-time Data, API

Abstract. Social Media datasets are playing a vital role to provide information that can support decision making in nearly all domains of technology. It is due to the fact that social media is a quick and economical approach for data collection from public through methods like crowdsourcing. It is already proved by existing research that in case of any disaster (natural or man-made) the information extracted from Social Media sites is very critical to Disaster Management Systems for response and reconstruction. This study comprises of two components, the first part proposes a framework that provides updated and filtered real time input data for the disaster management system through social media and the second part consists of a designed web user API for a structured and defined real time data input process. This study contributes to the discipline of design science for the information systems domain. The aim of this study is to propose a framework that can filter and organize data from the unstructured social media sources through recognized methods and to bring this retrieved data to the same level as that of taken through a structured and predefined mechanism of a web API. Both components are designed to a level such that they can potentially collaborate and produce updated information for a disaster management system to carry out accurate and effective.

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