An exploratory analysis of the text mining of news articles about “water and society”

This paper aims to discover the social interest in the issues of water and society from media reports and to compare it in Japanese and international media. This research uses the online databases of two newspapers: the Japan News and the International New York Times. They are used to understand the difference between the two newspapers. The social interest is discovered by cluster analysis that is, to drive clusters that have value with respect to the problem being addressed. Clustering divides the document collection into mutually exclusive groups based on the presence of similar themes. The articles extracted from those databases are analysed using a KH coder and the generated co-occurrenc