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

Abstract

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..

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