Extraction of Statistical Terms and Co-occurrence Networks from Newspapers

In this paper, we automatically extract statistical terms and build their co-occurrence networks from newspapers. Statistical terms are expression of the measurements of statistics to watch the movements of phenomena; birth rates, public approval rating of the Cabinet and so on. In recent years, we have a vast amount of available information because of computerization and the technologies of making their overview and enhancement of their values are noticed. One of them is the technology of visualizing information of social trend and movements from newspapers. For visualizing trend information, there some approaches. In this paper, we take the approach of building networks of causal relations among the statistical terms. To extract statistical terms, we propose extraction method using suffixes. To extract causal relations among statistical terms, we first extract co-occurrence relations and next show them with the networks. We can extract many statistical terms with high accuracy by our method and find interesting links among some statistical terms by our co-occurrence networks.