In this paper, we design a new method to explore the social context as community mappings from a buzz marketing site. In this method, after extracting significant topical terms from messages in buzz marketing sites, first we construct a snapshot co-occurrence network at each time stamp. Next, we organize topic hierarchical structures from each co-occurrence network by using the modularity. %% measures. Then, we exploire a community mapping as an LCA-preserving mapping between topic hierarchical structures and a topic mapping as a correspondence in a community mapping. Hence, we can extract a topic transition as topic mappingsfor the same topic. matching leveraging the distance computation. Finally, we give experimental results related to the East Japan Great Earthquake in the buzz marketing site.
