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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