By means of data mining techniques development these days, the knowledge discovered by virtue of data mining has ranging from business application to fraud detection. However, too often, we see only the profit-making justification for investing in data mining while losing sight of the fact that they can help resolve issues of global or national importance. In this research, we propose the architecture for issue oriented information construction and knowledge discovery that related to political or public policy issues. In this architecture, we adopt issue networks as the description model and data mining as the core technique. This study is also performed and verified with prototype system constructing and case data analyzing. There are three main topics in our research. The issue networks information construction starts with text files information retrieving of specified issue from news reports. Keywords retrieved from news reports are converted into structuralized network nodes and presented in the form of issue networks. The second topic is the clustering of network actors. We adopt an issue-association clustering method to provide views of clustering of issue participators based on relations of issues. In third topic, we use specified link analysis method to compute the importance of actors and sub-issues. Our study concludes with performance evaluation via domain experts. We conduct recall, precision evaluation for first topic above and certainty, novelty, utility evaluation for others.