Visual Exploration of Topics in Multimedia News Corpora

The increasing availability of digital multimedia content has led to the need of new approaches for the analysis of large databases containing video and associated data, for example, subtitles. Visualization provides valuable insights of such dataset, complementing approaches solely based on techniques for knowledge discovery in databases and information retrieval. Hence, visual analytics, combining automatic processing with interactive data visualization, has proven to be an effective means to explore and interpret such data. The analysis of news corpora represents a typical task for such a scenario. Domain experts such as journalists and social science scholars require an overview of important topics, the temporal coherence of events, and they should be able to compare different topics. We present a visual analytics approach that aims to support these tasks with automatic video preprocessing, topic extraction, clustering, and dimensionality reduction. Coordinated linked views support the flexible inspection of the dataset and the processed results. We further discuss the application of our approach in a usage scenario, inspecting the dataset of a daily news broadcast of the year 2015.