News agencies produce thousands of multimedia stories describing events happening in the world that are either scheduled such as sports competitions, political summits and elections, or breaking events such as military conflicts, terrorist attacks, natural disasters, etc. When writing up those stories, journalists refer to contextual background and to compare with past similar events. However, searching for precise facts described in stories is hard. In this paper, we propose a general method that leverages the Wikidata knowledge base to produce semantic annotations of news articles. Next, we describe a semantic search engine that supports both keyword based search in news articles and structured data search providing filters for properties belonging to specific event schemas that are automatically inferred.
This paper presents a novel open-source browser plug-in that aims at supporting journalists and news professionals in their efforts to verify user-generated video. The plug-in, which is the result of an iterative design thinking methodology, brings together a number of sophisticated multimedia analysis components and third party services, with the goal of speeding up established verification workflows and making it easy for journalists to access the results of different services that were previously used as standalone tools. The tool has been downloaded several hundreds of times and is currently used by journalists worldwide, after being tested by Agence France-Presse (AFP) and Deutsche Welle (DW) journalists and media researchers for a few months. The tool has already helped debunk a number of fake videos.
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