MoodViews: Tools for Blog Mood Analysis

We demonstrate a system for tracking and analyzing moods of bloggers worldwide, as reflected in the largest blogging community, LiveJournal. Our system collects thousands of blog posts every hour, performs various analyses on the posts and presents the results graphically. Exploring the Blogspace From the point of view of information access, the blogspace offers many natural opportunities beyond traditional search facilities, such as trend detection, topic tracking, link tracking, feed generation, etc. But there is more. Many blog authoring environments allow bloggers to tag their entries with highly individual (and personal) features. Users of LiveJournal, currently the largest weblog community, have the option of reporting their mood at the time of the post; users can either select a mood from a predefined list of 132 common moods such as “amused ” or “angry, ” or enter free-text. A large percentage of LiveJournal users chooses to utilize this option, tagging their postings with a mood. This results in a stream of hundreds of weblog posts tagged with mood information per minute, from hundreds of thousands of different users across the globe. Our focus in this demo is on providing access to the blogspace using moods as the “central” dimension. The type of information needs that we are interested in are best illustrated by questions such as: How do moods develop? How are they related? How do global events impact moods? And: Can global mood swings be traced back to global events? We describe MoodViews, a collection of tools for analyzing, tracking and visualizing moods and mood changes in blogs posted by LiveJournal users. MoodViews MoodViews tracks the stream of mood-annotated text made available by LiveJournal. At present, MoodViews consists of three components, each offering a different view of global mood levels, the aggregate across all postings of the variou