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        <title>Examining the Ordering of Rhetorical Strategies in Persuasive Requests</title>
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    <name type="personal">
        <namePart type="given">Omar</namePart>
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    <name type="personal">
        <namePart type="given">Jiaao</namePart>
        <namePart type="family">Chen</namePart>
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    <name type="personal">
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        <namePart type="given">Polo</namePart>
        <namePart type="family">Chau</namePart>
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    <name type="personal">
        <namePart type="given">Diyi</namePart>
        <namePart type="family">Yang</namePart>
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        <name type="personal">
            <namePart type="given">Yang</namePart>
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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.</abstract>
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    <identifier type="doi">10.18653/v1/2020.findings-emnlp.116</identifier>
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%0 Conference Proceedings
%T Examining the Ordering of Rhetorical Strategies in Persuasive Requests
%A Shaikh, Omar
%A Chen, Jiaao
%A Saad-Falcon, Jon
%A Chau, Polo
%A Yang, Diyi
%Y Cohn, Trevor
%Y He, Yulan
%Y Liu, Yang
%S Findings of the Association for Computational Linguistics: EMNLP 2020
%D 2020
%8 November
%I Association for Computational Linguistics
%C Online
%F shaikh-etal-2020-examining
%X 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.
%R 10.18653/v1/2020.findings-emnlp.116
%U https://aclanthology.org/2020.findings-emnlp.116
%U https://doi.org/10.18653/v1/2020.findings-emnlp.116
%P 1299-1306

Markdown (Informal)

[Examining the Ordering of Rhetorical Strategies in Persuasive Requests](https://aclanthology.org/2020.findings-emnlp.116) (Shaikh et al., Findings 2020)

• Examining the Ordering of Rhetorical Strategies in Persuasive Requests (Shaikh et al., Findings 2020)

ACL

• Omar Shaikh, Jiaao Chen, Jon Saad-Falcon, Polo Chau, and Diyi Yang. 2020. Examining the Ordering of Rhetorical Strategies in Persuasive Requests. In Findings of the Association for Computational Linguistics: EMNLP 2020, pages 1299–1306, Online. Association for Computational Linguistics.