In this paper, we propose a visualization method for global dynamics. Global dynamics of various events and statistics are important to analyze complex international issues such as environmental, economic and political problems. We have been developing a system which can extract a co-occurrence network of statistical terms based on a suffix pattern matching. However, the network structure consisting of thousands of statistical terms is too complicated to understand their causal relations briefly. So we propose a method for simplifying the network structure based on network complexity and language expressions. Our experimental result shows that a clique of the statistical terms corresponds to a certain topic or issue and causal relations can be described as a chain of the cliques on
['Hideki Kawai', 'Kazuo Kunieda', 'Keiji Yamada', 'H. Saito', 'Masaaki Tsuchida', 'Hironori Mizuguchi']
Visualization for Statistical Term Network in Newspaper