Examining the Ordering of Rhetorical Strategies in Persuasive Requests
This work addresses persuasion optimization for domains like advertising and argumentation, but it is incremental as it builds on existing methods for analyzing textual strategies.
The study investigated how the ordering of rhetorical strategies affects persuasiveness in textual loan requests, finding that specific orderings interact uniquely with content to impact success rates.
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.