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Examining the Ordering of Rhetorical Strategies in Persuasive Requests

2020-10-09 · Findings of the Association for Computational Linguistics 2020 · Omar Shaikh, Jiaao Chen, Jon Saad-Falcon, Duen Horng Chau, Diyi Yang

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.

📄 PDF Abstract BibTeX arXiv:2010.04625

Code (1)

GT-SALT/Persuasive-Orderings 공식 구현 pytorch

Tasks

Persuasiveness

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Tanh Activation 설명 없음
Sigmoid Activation 설명 없음
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LSTM An LSTM is a type of recurrent neural network that addresses the vanishing gradient problem in vanilla…

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