Abstract: Cyberspace has turned into the "second battlefield" for security prevention and control. How to provide technical support for crime early warning in the new battlefield has become one of most important part of security work. A modeling method based on social viewpoint is proposed by analyzing text features of cyber-crime. Firstly, the top-level ontology of cyber-crime is constructed by extracting knowledge from the experiences of domain experts in solving cases, and domain ontologies extending top-level ontology are constructed according to policy categories. Secondly, with theme crawlers, opinions classified by subjects focused by police from official websites are collected, and correlative social viewpoints are built. Finally, by ontology instance reasoning, each speech from social media is matched to corresponding social viewpoint, and by similarity calculation a judgment of early warning is predicted. By analyzing five sets of results from emotion-based and viewpoint-based cyber-crime early warning experiments, it turns out that the text of cyber-crime is non-emotional sensitivity, however, the viewpoint-based modeling method can predict the truly cyber-crimes effectively.

Key words: cyber-crime, early warning, social viewpoint, ontology