Smith, A., Malik, S., Shneiderman, B. (December 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.