A research team from the Department of Computer Science and Engineering, Indian Institute of Technology, Kharagpur (IIT-K) developed an algorithm for effective management of disaster time social-media posts in a bid to effectively manage the disaster.
The recent earthquakes in Nepal and floods in Kerala have proved the inevitability of social media platforms as they have become essential sources of real-time information regarding disasters. The victims, on-site volunteers and empathisers all of whom act as ‘social sensors’ are the ones that provide information.
However, the vast volume of flow and arbitrary nature of the content makes it challenging to locate relevant information. The social media posts often contain informal language without any grammar, arbitrary shortening of words and images.
The algorithm, therefore, attempts to sort the variegated, overwhelming number of social media posts during disasters. This can help real-time disaster-related news to reach the right places.
The algorithm developed by IITK can search for various social media platforms, especially micro-blogging sites, with broad access, and report on situational information.
The research team has employed ‘Neural Network and Deep Learning’ models to understand social media text which can often contain shortened words, images or informal information. It can also filter rumours and hate posts. The team is also developing web-based systems and mobile apps for aiding post-disaster relief operations.