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The use of Internet media data for the early detection and situational awareness of infectious disease events has evolved into a globally recognized field. Internet media has the advantage of being timely -- available in any language from local to international sources. Published success stories include tracking events associated with mass gatherings, pandemic influenza, the aftermath of natural disasters, food shortages and plant pest and disease outbreaks. However, sifting through the vast array of information on the Internet, ranging from traditional text media to social media is challenging, e.g., detecting a significant signal among the vast noise of misinformation and non-specific reports. In addition, identifying anomalous activity without an established baseline of media activity for a given disease in a particular region is difficult. Recognizing false positive and false negative events is also problematic due to the lack of official reports or delays in diagnostic testing. As such, applying traditional epidemiological analytical approaches to Internet data is often not possible. Despite these obstacles, many recent advances in the field, such as mapping of Internet data using visual analytic tools, forecast modeling and social networking analysis have demonstrated the great potential of media as a real-time complimentary approach to traditional public health methods of disease surveillance.<p><p>Keywords: