Conference Proceedings

Joint Sentence-Document Model for Manifesto Text Analysis

Shivashankar Subramanian, Trevor Cohn, Timothy Baldwin, Julian Brooke

Proceedings of the Australasian Language Technology Association Workshop, ALTA 2017, Brisbane, Australia, December 6-8, 2017 | Queensland University of Technology | Published : 2017


Election manifestos document the intentions, motives, and views of political parties. They are often used for analysing party policies and positions on various issues, as well as for quantifying a party’s position on the left–right spectrum. In this paper we propose a model for automatically predicting both types of analysis from manifestos, based on a joint sentence–document approach which performs both sentence-level thematic classification and document-level position quantification. Our method handles text in multiple languages, via the use of multilingual vector-space embeddings. We empirically show that the proposed joint model performs better than state-of-art approaches for the docume..

View full abstract