  This paper considers the problem of characterizing stories by inferring
properties such as theme and style using written synopses and reviews of
movies. We experiment with a multi-label dataset of movie synopses and a tagset
representing various attributes of stories (e.g., genre, type of events). Our
proposed multi-view model encodes the synopses and reviews using hierarchical
attention and shows improvement over methods that only use synopses. Finally,
we demonstrate how can we take advantage of such a model to extract a
complementary set of story-attributes from reviews without direct supervision.
We have made our dataset and source code publicly available at
https://ritual.uh.edu/ multiview-tag-2020.
