  A news article's title, content and link structure often reveal its political
ideology. However, most existing works on automatic political ideology
detection only leverage textual cues. Drawing inspiration from recent advances
in neural inference, we propose a novel attention based multi-view model to
leverage cues from all of the above views to identify the ideology evinced by a
news article. Our model draws on advances in representation learning in natural
language processing and network science to capture cues from both textual
content and the network structure of news articles. We empirically evaluate our
model against a battery of baselines and show that our model outperforms state
of the art by 10 percentage points F1 score.
