Mining web query logs to analyze political issues

Abstract

We present a novel approach to using anonymized web search query logs to analyze and visualize political issues. Our starting point is a list of politically annotated blogs (left vs. right). We use this list to assign a numerical political leaning to queries leading to clicks on these blogs. Furthermore, we map queries to Wikipedia articles and to fact-checked statements from politifact.com, as well as applying sentiment analysis to search results. With this rich, multi-faceted data set we obtain novel graphical visualizations of issues and discover connections between the different variables.