DiversiNews: Surfacing Diversity in Online News


  • Mitja Trampuš Jozef Stefan Institute
  • Flavio Fuart Jozef Stefan Institute
  • Daniele Pighin Google Inc.
  • Tadej Štajner Jozef Stefan Institute
  • Jan Berčič Jozef Stefan Institute
  • Blaz Novak Jozef Stefan Institute
  • Delia Rusu Jozef Stefan Institute
  • Luka Stopar Jozef Stefan Institute
  • Marko Grobelnik Jozef Stefan Institute




online news, media bias, news aggregation, data exploration, computer-aided discovery


For most events of at least moderate significance, there are likely tens, often hundreds or thousands of online articles reporting on it, each from a slightly different perspective. If we want to understand an event in depth, from multiple perspectives, we need to aggregate multiple sources and understand the relations between them. However, current news aggregators do not offer this kind of functionality. As a step towards a solution, we propose DiversiNews, a real-time news aggregation and exploration platfom whose main feature is a novel set of controls that allow users to contrast reports of a selected event based on topical emphases, sentiment differences and/or publisher geolocation. News events are presented in the form of a ranked list of articles pertaining to the event and an automatically generated summary. Both the ranking and the summary are interactive and respond in real time to user’s change of controls. We validated the concept and the user interface through user tests with positive results.

Author Biography

Mitja Trampuš, Jozef Stefan Institute




How to Cite

Trampuš, M., Fuart, F., Pighin, D., Štajner, T., Berčič, J., Novak, B., Rusu, D., Stopar, L., & Grobelnik, M. (2015). DiversiNews: Surfacing Diversity in Online News. AI Magazine, 36(4), 87-104. https://doi.org/10.1609/aimag.v36i4.2528