Cyber-Trafficking is the illegal transport of humans, drugs, weapons, or goods by means of Internet-enabled electronic devices. Currently, there is a lack of surveillance and understanding of the rapidly growing social concern about cyber-Trafficking (CT). This paper describes the Cyber-Trafficking Surveillance System (CyTraSS) and provides preliminary findings of using the system to monitor CT social media discussions. CyTraSS supports flexible collection, analysis, and visualization of social media content, user linkage, and temporal features. The CyTraSS database contains a focused collection of over 2,318,691 social media messages posted by over 740,070 users who discussed about trafficking crimes and issues. CyTraSS supports keyword search, sentiment analysis, message statistics summarization, and influential leader identification. Emotion expressed in social media messages is extracted and aggregated quantitatively to indicate community mood. We examined three use cases about a sex trafficker identified by a flight attendant, Federal use of private prisons, and trafficking cases related to Beijing. These time-sensitive incidents are highly-relevant to CT and were identified by using clues provided by CyTraSS. The results have strong implications for understanding CT concern on social media.