DiversiNews: Surfacing Diversity in Online News
Keywords: online news, media bias, news aggregation, data exploration, computer-aided discovery
AbstractFor 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.
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
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