Generating A Visual Overview Of Large Diachronic Document Collections Based On The Detection Of Topic Change

Large digital diachronic document collections are a central source of information in science, business, and for the general public. One challenge for the efficient visualization of these collections is the automatic calculation and visualization of the main topics. These topics can then serve as the basis for an overview of the content and any subsequent interactive visual analysis. We introduce the new language processing concept of volatility of terms measured as the change of the context of terms. We demonstrate that volatility can serve as an excellent basis for the visual overview of large collections using two different examples.