Work

Target Based Speech Act Classification in Political Campaign Text

Year: 2019

Type: conference-paper

Abstract: We study pragmatics in political campaign text, through analysis of speech acts and the target of each utterance.We propose a new annotation schema incorporating domainspecific speech acts, such as commissiveaction, and present a novel annotated corpus of media releases and speech transcripts from the 2016 Australian election cycle.We show how speech acts and target referents can be modeled as sequential classification, and evaluate several techniques, exploiting contextualized word representations, semi-supervised learning, task dependencies and speaker meta-data.

Source: Joint Conference on Lexical and Computational Semantics

DOI: 10.18653/v1/s19-1030

Authors: Shivashankar Subramanian, Trevor Cohn, Timothy Baldwin

Institution: The University of Melbourne

Language: English

Topic: Natural Language Processing Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funders: Australian Government, Australian Research Council

OpenAlex ID: W2945473303