The invention discloses a visual behavior-based online user type identification method and system, which collects and processes the eye movement data of one or more different types of users, obtains a gaze information data set and a user type set, and according to the gaze information data set Gaze information, obtain one or more eye movement feature data to form a sampling data set, select eye movement feature data from it and input it into a support vector machine, train to obtain a user type classifier, complete the machine learning process to obtain a classifier, and collect any online The user's eye movement data is input to the trained user type classifier, and the user type of any user on the Internet is identified according to the classifier. Mainly use eye-tracking technology to obtain and calculate three types of eye-movement characteristic data when users browse the web, and judge the type of online users according to the difference in eye-movement characteristic data. User identification based on visual behavior can actively record the eye movement data of online users, and the extraction of data is simple and reliable, with high accuracy and reliability.