GATE team wins first prize in the Hyperpartisan News Detection Challenge
SemEval 2019 recently launched the Hyperpartisan News Detection Task. It’s focus was to evaluate how well tools could automatically classify hyperpartisan news texts.
Entrants needed to create a system that could analyse a piece of news text. The systems must be able to “decide whether it follows a hyperpartisan argumentation, i.e. whether it exhibits blind, prejudiced, or unreasoning allegiance to one party, faction, cause, or person.”
Congratulations to Grantham Scholar Ye Jiang who was part of the winning team!
In total, 322 teams registered to take part, of which 42 actually submitted an entry, including the GATE team consisting of Ye Jiang, Xingyi Song and Johann Petrak, with guidance from Kalina Bontcheva and Diana Maynard.
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