  We present a new similarity measure tailored to posts in an online forum. Our
measure takes into account all the available information about user interest
and interaction --- the content of posts, the threads in the forum, and the
author of the posts. We use this post similarity to build a similarity between
users, based on principal coordinate analysis. This allows easy visualization
of the user activity as well. Similarity between users has numerous
applications, such as clustering or classification. We show that including the
author of a post in the post similarity has a smoothing effect on principal
coordinate projections. We demonstrate our method on real data drawn from an
internal corporate forum, and compare our results to those given by a standard
document classification method. We conclude our method gives a more detailed
picture of both the local and global network structure.
