Combining Social Media and Authoritative Data towards identifying useful Information for Disaster Management

A Study on the Twitter usage in the River Elbe Flood of June 2013

In recent years, social media emerged as a potential resource to improve the management of crisis situations such as disasters triggered by natural hazards. Although there is a growing research body concerned with the analysis of the usage of social media during disasters, most previous work has concentrated on using social media as a stand-alone information source, whereas its combination with other information sources holds a still underexplored potential. A recent article presents an approach to enhance the identification of relevant messages from social media that relies upon the relations between georeferenced social media messages as Volunteered Geographic Information and geographic features of flood phenomena as derived from authoritative data (sensor data, hydrological data and digital elevation models).
We apply this approach to examine the micro-blogging text messages of the Twitter platform (tweets) produced during the River Elbe Flood of June 2013 in Germany. This is performed by means of a statistical analysis aimed at identifying general spatial patterns in the occurrence of flood-related tweets that may be associated with proximity to and severity of flood events. The results show that messages near (up to 10 km) to severely flooded areas have a much higher probability of being related to floods. In this manner, it can be concluded that the geographic approach proposed here provides a reliable quantitative indicator of the usefulness of messages from social media by leveraging the existing knowledge about natural hazards such as floods, thus being valuable for disaster management in both crisis response and preventive monitoring.

More Info:
Porto de Albuquerque, J., B. Herfort, A. Brenning, A. Zipf (2015): A Geographic Approach for Combining Social Media and Authoritative Data towards Improving Information Extraction for Disaster Management. International Journal of Geographical Information Science, volume and issue pending, pp. pending. Taylor & Francis. DOI: 10.1080/13658816.2014.996567.