Internet events are public events with the participation of netizens to express their opinions or comments. As an emerging Internet social phenomenon, Internet events often draw nationwide attention and eventually influence offline events. Netizen groups who participate in the Internet events play a central role in such events. Netizen group’s opinions and attitudes, which represent online public opinion, are the key factors to influence the evolution of Internet events. Social modeling of netizen groups, especially the dynamics of their opinions in Internet events, can help us understand the mechanism and evolvement of such events and provide valuable insights for social management and decision making. In this paper, we focus on the study of netizen groups and the dynamics of their opinions, and propose an agent-based model to capture the interactions in domain-oriented Internet events and their influence on the dynamics of netizen group’s states. Our experiment is based on two case studies of Chinese Internet events. We test the proposed model by running simulations and comparing experimental results with real social media data to show the effectiveness of our model. However, traditional hand-crafted agent-based model construction needs much human efforts and is time consuming. To partially alleviate this pain staking process, in this paper, we propose to employ computational techniques to extract domain knowledge from online textual data of historical events to facilitate the construction of agent-based model and illustrate the methods in food safety Internet events. First, we adopt multiple natural language processing techniques to extract the actions of every party from news reports of historical Internet events and construct the action library of the agents. The experimental results verify the effectiveness of the method. Second, we propose an approach to extract netizens’ opinions from comments of Internet events and summarize them to obtain netizen group’s opinions to support for model’s construction. It performs well in our experimental study. Last, we rectify the interaction rules in the model by analyzing the association between the interactions in Internet events and the dynamics of netizen group’s opinions. Finally, we reconstruct the agent-based model of netizen groups using the domain knowledge acquired by computational techniques, and compare its simulation results on real food safety Internet events with the hand-made model. Expe...
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