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      Examining the Ordering of Rhetorical Strategies in Persuasive Requests

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          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.

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          Author and article information

          Journal
          09 October 2020
          Article
          2010.04625
          91b3a7db-8f40-490e-bce5-f73bcd38ce11

          http://arxiv.org/licenses/nonexclusive-distrib/1.0/

          History
          Custom metadata
          Findings of EMNLP 2020
          cs.CL cs.AI cs.LG

          Theoretical computer science,Artificial intelligence
          Theoretical computer science, Artificial intelligence

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