User Evaluation of a System for Classifying and Displaying Political Viewpoints of Weblogs

Abstract

This paper presents a Web-based user evaluation of a system for classifying and presenting political viewpoints of blog posts. The system is based on a classification model trained using a supervised learning algorithm, and the data set consists of recent posts from blogs that are self-identified as a liberal or a conservative viewpoint. We first discuss the classification process. Then, with a prototype system for retrieving and classifying political blogs, we look at how the classification results can be presented to users in order to improve the blog search experience. We describe an online user study with 15 users, and the study shows that users preferred the search results page that clearly shows the political viewpoint classification.