Scientific messages in peer reviewed academic research papers often inform government health policies, these are communicated to the news media for public broadcasting. However increasingly social media is playing a significant role in disseminating public health messages. This dramatically enhances the prominence of highly publicized media topics and the public awareness of these topics. This is a largely unregulated space with the potential to influence mistrust, misinformation and cause low confidence in public health messaging. We will provide a reliable classifier to detect message distortion to protect the general public and to ensure they receive accurate and valid information.