Examining the Ordering of Rhetorical Strategies in Persuasive Requests

Omar Shaikh, Jiaao Chen, Jon Saad-Falcon, Polo Chau, Diyi Yang


Abstract
Interpreting how persuasive language influences audiences has implications across many domains like advertising, argumentation, and propaganda. Persuasion relies on more than a message’s content. Arranging the order of the message itself (i.e., ordering specific rhetorical strategies) also plays an important role. To examine how strategy orderings contribute to persuasiveness, we first utilize a Variational Autoencoder model to disentangle content and rhetorical strategies in textual requests from a large-scale loan request corpus. We then visualize interplay between content and strategy through an attentional LSTM that predicts the success of textual requests. We find that specific (orderings of) strategies interact uniquely with a request’s content to impact success rate, and thus the persuasiveness of a request.
Anthology ID:
2020.findings-emnlp.116
Volume:
Findings of the Association for Computational Linguistics: EMNLP 2020
Month:
November
Year:
2020
Address:
Online
Venues:
EMNLP | Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1299–1306
Language:
URL:
https://www.aclweb.org/anthology/2020.findings-emnlp.116
DOI:
10.18653/v1/2020.findings-emnlp.116
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PDF:
http://aclanthology.lst.uni-saarland.de/2020.findings-emnlp.116.pdf