Interested citizens use the Internet for, among other purposes, expressing their opinions and views about political issues and local concerns. There is much expression by citizens in web logs (or blogs). Blogs are a form of individual expression, publicly available and constantly updated. Blog entries may contain a variety of topics of discussion. Two topics are the focus of this thesis: political and local issues. Often blogs are aggregated into regional collections. These aggregated sites are a good source for local and regional discussions. However, because the discussions are only implicitly connected, tools are needed to identify similarity in otherwise individual blog entries. Blog visualizations can help address this problem. We have created a tool, VizBlog that supports the task of local blog discussion discovery. This blog visualization tool visually presents information in a way that helps users identify blog entry clusters of similar content, helps citizens find other citizens opinions, and also helps government officials identify local hot issues. This research seeks to: a) validate the accuracy of the automated similarity classification done by VizBlog; b) evaluate the usability of VizBlog; and c) study the characteristics of local conversations scattered in a series of regional blogs. The results of the evaluation showed that VizBlog did make it easy for users to identify topics of interest from the visualization, in addition to providing insight on ongoing discussion taking place in regional blogs. In addition, the automated similarity computation was validated when compared to classification done by humans. Finally, the thesis discusses the findings of the structure of the regional blogosphere. / Master of Science