To appear in: Lecture Notes on Social Network Analysis, Springer (2013).
Topic models are regularly used to provide directed exploration
and a high-level overview of a corpus of unstructured text. In many cases, it is
important to analyze the evolution of topics over a time range. In this work,
we present an application of statistical topic modeling and alignment (binned
topic models) to group related documents into automatically generated topics
and align the topics across a time range. Additionally, we present TopicFlow,
an interactive tool to visualize the evolution of these topics. The tool was
developed using an iterative design process based on feedback from expert
reviewers. We demonstrate the utility of the tool with a detailed analysis of
a corpus of data collected over the period of an academic conference, and
demonstrate the effectiveness of this visualization for reasoning about large
data by a usability study with 18 participants.