ControCurator: Crowds and Machines for Controversy Discovery and Modeling

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This is a joined project with Lora Aroyo (VU), Sound & Vision and Crowdynews funded by Commit on identifying controversial topics in multi-model data, with applications ranging from health, to political discourse, news, etc.
The ControCurator project aims to enable modern information access systems to discover and understand controversial topics and events by bringing together different types of crowds (niches of experts, lay crowds and engaged social media contributors) and machines in a joint active learning workflow for the creation of adequate training data (real-time and offline).
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