The Silicon Review
20 November, 2018
A new solution is being developed by the Indian Institute of Technology Kharagpur to determine fake news about disasters on social media platforms like Facebook, Twitter, and WhatsApp.
The solution is based on AI (artificial intelligence), and it removes critical information from the social media websites that are hard to carryout manually. It will also determine the post’s authenticity and pass on data to help relief and rescue operations.
According to Saptarshi Ghosh, IIT Kharagpur, the solution utilizes deep machine learning algorithms and it can determine fake news and can even alert users in the time of disasters. The solution has the potential to determine fake news or rumours and is limited only to disasters and it will provide at least 90 percent accurate results in determining fake news from real.
The solution will also help the disaster victims in terms of collecting information.
According to sources, in Twitter, only 2 percent of the tweets on disasters are relevant and the rest of the post is mostly conversations, sympathy for victims.
Mr. Ghosh is heading the team developing algorithms for the solution.
The solution experimented during the 2015 Nepal earthquake and 2016 Chennai Floods on WhatsApp and Twitter. The fundings for the complete project were given by Microsoft Research India, IIT Kharagpur Institute Scheme for Innovative Research and Development grant, and Media Labs Asia and Department of Electronics and Information Technology.
About the solution
In the case of a disaster, if any user posts the situation of victims hit by a cyclone, earthquake, etc. in English and Hindi, after that, the relevant information will be sent to the nearby relief camps through a computer programme.
IIT Kharagpur and its collaborators have submitted an idea regarding the solution to Microsoft Research India at Qatar Computing Research Institute (QCRI). IIT Kharagpur will join hands with Microsoft Research and QCRI if the idea gets accepted. After that, the premium institute can develop the systems for aiding post-disaster relief operations.
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