Partisan News Media Using Weakly Supervised Learning
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Characterizing Online Criticism of Partisan News Media Using Weakly Supervised Learning
Announce Type: new Abstract: We propose novel methods to identify tweets that criticize partisan news sources. Prior work suggests that criticism, ridicule, and distrust of news media all play important roles in hyperpartisanship, misinformation, and filter bubble formation. Thus, understanding the prevalence and temporal dynamics of media-targeted criticism can provide us with updated tools to assess the health of the information ecosystem.