GATE team wins first prize in the Hyperpartisan News Detection Challenge
SemEval 2019 recently launched the Hyperpartisan News Detection Task in order to evaluate how well tools could automatically classify hyperpartisan news texts. The idea behind this is that “given a news text, the system must decide whether it follows a hyperpartisan argumentation, i.e. whether it exhibits blind, prejudiced, or unreasoning allegiance to one party, faction, cause, or person.”
Grantham Scholar Ye Jiang was part of the winning team.
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