Acquiring netizen group's opinions for modeling food safety events

Food safety events are typical public security events that draw great public concern. In food safety events, millions of netizens pay close attention to the event, express their opinions online and thus influence the decisions of government or food producers. Modeling netizen groups, especially the dynamics of their opinions in these events, can help us understand the mechanism and evolvement of such events and provide valuable insights for social management. However, conventional computational models, such as agent-based models, are usually constructed manually. In this paper, we propose an approach to acquiring netizen group's opinions from online comments to facilitate the modeling of food safety events. We conduct experimental study on typical events happened in China and empirically evaluate the performance of our proposed approach. The results verify the effectiveness of the approach.