Spamming persists as a problem in Social Networking Sites (SNS). About 8.7\% of the total accounts of Facebook are fake or duplicate. These fake accounts are spreading rumors. Facebook believes 14.3 million of these accounts were created for spamming. Sometimes these accounts are being used to fulfil personal vendetta. Using spam filters seems to be insufficient as Facebook is struggling to clean up the spam while users are falling in traps like clickbait. On the other hand rumors in SNS causing severe trouble on a large scale. In recent time a violent incident took place in Ramu, Bangladesh on the basis of a rumor spread through Facebook. Rumors like this affecting us as individuals, our society. The main challenge of a rumor detection tool is the accuracy of the system and the time it takes to give the results. An accuracy having 90\% accuracy may not be enough in the time of natural disasters or war as remaining 10\% can cause havoc. Again if the system takes too much time no matter what the result is, it may be too late. We designed a tool which can quickly detect if a post is a spam or rumor. This tool responds to a user query for a post and try to verify the authenticity of a post with the help of Facebook community. This tool is designed to give a quick verdict so that it can be useful to prevent a viral malcontent in Social Networking sites. We implemented this tool on Facebook. We used Facebook Graph API to select groups of users with relevant knowledge about the topic who can contribute to determine the authenticity of the post.

Accepted in 3rd Asia-Pacific World Congress on CSE 2016, Fiji, Dec 4-6, 2016.