Hyperpartisan News Detection Challenge 1st prize won by GATE team. Congratulations to Grantham Scholar Ye Jiang who was part of the winning team!
SemEval 2019 recently launched the Hyperpartisan News Detection Challenge. 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.’
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.
Read more here.
Ye Jiang’s research looks at the correlations between natural disasters, climate change, and the reporting and understanding of such events. If you want to find out more about Ye Jiang’s work, then you can check out his profile page.
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