Early investigation of proposed hoax detection for decreasing hoax in social media

Social Media allow people to communicate over long distance and increase the users for the past years. However the threat of Hoax is also increasing in social media which increase the risk of mass panic, where the society become confuse between false and true, other words between hoax and not hoax. To mitigate the effect of hoax, a system to filter out hoax posts from social media is proposed. We propose a system framework that might be able to filter out hoax from social media post feeds in order to reduce the amount of hoax posts in social media. It is difficult to reduce 100% hoax from social media, but at least there is a technology which can decrease the hoax in social media. This system works by utilizing data mining to search past hoax records and analyze the post data pattern to determine whether a post is a hoax or not hoax. Our proposed system will also utilize social media Application Program Interface (API) such as news, facebook, twitter, in order to find similar writing in other social media or news website to find out the authenticity of a person's post.