Influenza surveillance is essential for detecting and managing outbreaks. The Maryland Department of Health and Mental Hygiene (DHMH) currently includes the number of emergency room and physician visits for influenza-like-illness (ILI) to track flu activity. Recently, internet and social media based surveillance methods have emerged as useful in detecting outbreaks. This study aims to determine if internet and social media based surveillance methods are useful in monitoring ILI in Maryland through assessing how Google Flu Trends (GFT) and tweets compare to portions of DHMH’s formal reporting system. Innovations of this study include using symptom based keywords and incorporating a variety of sources of surveillance data. Results show tweets had a strong positive correlation with all other surveillance sources, Pearson’s correlation coefficients ranged from 0.62-0.68. GFT were more highly correlated with DHMH data. Further research should investigate automating collection of tweets, application to other diseases, and standardized methods for location determination.