TY - GEN
T1 - Asking too much? The rhetorical role of questions in political discourse
AU - Zhang, Justine
AU - Spirling, Arthur
AU - Danescu-Niculescu-Mizil, Cristian
N1 - Funding Information:
Acknowledgements. The first author thanks John Bercow, the Speaker of the House, for suggesting she “calm [her]self down by taking up yoga” during the hectic deadline push (https://youtu.be/AiAWdLAIj3c). The authors thank the anonymous reviewers and Liye Fu for their comments and for their helpful questions. We are grateful to the organizers of the conference on New Directions in Text as Data for fostering the inter-disciplinary collaboration that led to this work, to Amber Boydstun and Philip Resnik for their insights on questions in the political domain, and to Stephen Bates, Peter Kerr and Christopher Byrne for sharing the labeled PMQ dataset. This research has been supported in part by a Discovery and Innovation Research Seed Award from the Office of the Vice Provost for Research at Cornell.
Funding Information:
The first author thanks John Bercow, the Speaker of the House, for suggesting she ?calm [her]self down by taking up yoga? during the hectic deadline push (https://youtu.be/AiAWdLAIj3c). The authors thank the anonymous reviewers and Liye Fu for their comments and for their helpful questions. We are grateful to the organizers of the conference on New Directions in Text as Data for fostering the inter-disciplinary collaboration that led to this work, to Amber Boydstun and Philip Resnik for their insights on questions in the political domain, and to Stephen Bates, Peter Kerr and Christopher Byrne for sharing the labeled PMQ dataset. This research has been supported in part by a Discovery and Innovation Research Seed Award from the Office of the Vice Provost for Research at Cornell.
Publisher Copyright:
© 2017 Association for Computational Linguistics.
PY - 2017
Y1 - 2017
N2 - Questions play a prominent role in social interactions, performing rhetorical functions that go beyond that of simple informational exchange. The surface form of a question can signal the intention and background of the person asking it, as well as the nature of their relation with the interlocutor. While the informational nature of questions has been extensively examined in the context of question-answering applications, their rhetorical aspects have been largely understudied. In this work we introduce an unsupervised methodology for extracting surface motifs that recur in questions, and for grouping them according to their latent rhetorical role. By applying this framework to the setting of question sessions in the UK parliament, we show that the resulting typology encodes key aspects of the political discourse—such as the bifurcation in questioning behavior between government and opposition parties—and reveals new insights into the effects of a legislator’s tenure and political career ambitions.
AB - Questions play a prominent role in social interactions, performing rhetorical functions that go beyond that of simple informational exchange. The surface form of a question can signal the intention and background of the person asking it, as well as the nature of their relation with the interlocutor. While the informational nature of questions has been extensively examined in the context of question-answering applications, their rhetorical aspects have been largely understudied. In this work we introduce an unsupervised methodology for extracting surface motifs that recur in questions, and for grouping them according to their latent rhetorical role. By applying this framework to the setting of question sessions in the UK parliament, we show that the resulting typology encodes key aspects of the political discourse—such as the bifurcation in questioning behavior between government and opposition parties—and reveals new insights into the effects of a legislator’s tenure and political career ambitions.
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U2 - 10.18653/v1/d17-1164
DO - 10.18653/v1/d17-1164
M3 - Conference contribution
AN - SCOPUS:85063109682
T3 - EMNLP 2017 - Conference on Empirical Methods in Natural Language Processing, Proceedings
SP - 1558
EP - 1572
BT - EMNLP 2017 - Conference on Empirical Methods in Natural Language Processing, Proceedings
PB - Association for Computational Linguistics (ACL)
T2 - 2017 Conference on Empirical Methods in Natural Language Processing, EMNLP 2017
Y2 - 9 September 2017 through 11 September 2017
ER -