Visualizing Spatial-Temporal Evaluation of News Stories
Julia Sheidin, Joel Lanir, Tsvi Kuflik, Peter Bak · 2017
News today are generated and distributed online by a multitude of sources all over the world. Easy and efficient monitoring and analysis of news stories is of interest to both professional analysts and the general public. One interesting aspect is the magnitude and impact of a story as well as its evolution over time. In this work we introduce an idea and a system that presents temporal and spatial evolution of news world-wide, in two different levels, to help users quickly understand and act upon the large amount of data. An overview option shows a general split of the reported news, and a more detailed view provides interactive options for deeper analysis of a single news episode. We demonstrate our system on data from news events generated by the Europe Media Monitor (EMM), an online news aggregator platform.