Data sets from Carrizosa, Guerrero, Hardt and Romero Morales (2017) \"On Building Online Dynamic Visualization Maps for News Data Streams\" (article/paper under submission)

In this paper we develop an online tool to visualize news data over a time horizon. First, we perform a Natural Language Processing analysis, where the words are extracted, and their attributes, namely the importance and the relatedness, are calculated. Second, we present a Mathematical Optimization model for the visualization problem and a numerical optimization approach. The model represents the words using circles, whose time-varying area displays the importance of the word in each time period. The location of the words in the visualization region is guided by three criteria, namely, the accurate representation of the relatedness, the spread of the words in the visualization region to improve the quality of the visualization, as well as the visual stability over the time horizon. Our approach is flexible, allows user interaction and is scalable. We show results for three case studies using data from Danish news sources.