Examining the Ordering of Rhetorical Strategies in Persuasive Requests (2020)

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.

## introduction persuasion has been shown as a powerful tool for catalyzing beneficial social and political changes @xcite or enforcing propaganda as a tool of warfare @xcite . modeling persuasiveness of text has received much recent attention in the language community @xcite @xcite @xcite . numerous qualitative studies have been conducted to understand persuasion, from explorations of rhetoric in presidential campaigns @xcite to the impact of a communicator's likability on persuasiveness @xcite . studies of persuasion and argumentation that have analyzed textual level features (e.g., n-grams, independent rhetorical strategies) to gauge efficacy have also garnered recent attention @xcite @xcite @xcite . of particular interest is @xcite , which identified sentence ## interplay of ordering and content to examine how different strategy orderings contribute to overall persuasiveness of requests, we identified relationships between strategy orderings and success rate by analyzing learned attention weights between strategy orderings and content in our model. motivated by the "rule of three" prevalent in persuasive writing (clark, 2016), we utilized triplets as our strategy unit of analysis. the most important strategy triplet in each request was considered to be its "persuasion strategy triplet." pinpointing strategy triplets involved finding the most important consecutive three sentences ((z m-1 , l m-1 ), (z m , l m ), (z m+1 , l m+1 )) in one request based on highest request-level (α d ) attention weight associated with a sentence. the strategies (l m-1 , l m , l m+1 ) associated with these sentences were defined as the aforementioned strategy triples. we noted that the cumulative request-level (α d ) attention placed on strategy triplets had µ = .98 and σ = .07, indicating that a single triplet carried most responsibility for persuasiveness of requests. for our analysis, we also defined success rate of a strategy triplet as the average success rate of the requests it belongs to, irrespective of how important it is to a request (ignoring α d ). to control for infrequent triplets, we defined rare strategies as consisting of less than 0.5% of our dataset. we filtered these rare strategies, along with triplets containing the undefined "other" strategy. finally, we averaged sentence-level attention weights α s on each strategy representation in a triplet to represent the importance of an ordering pattern compared to content. figure 2 plots sentence-level attention weights for each strategy triplet and its corresponding success rate. we made three discoveries. (1) success rate and triplet attention were strongly negatively correlated (@xmath0.90, @xmath1.0001). therefore, the model paying larger attention to strategy triplets may communicate a request's lack of persuasiveness. (2) attention from around strategy (sos, im, re) onward decreased substantially, suggesting that content (complementary to strategy attention) played an increasingly larger role in determining the persuasiveness for strategies triplets above average success rate. a common pattern among the top 5 strategy triplets is the use of politeness. oftentimes, the politeness triplet appears at the end of the sentence and is usually paired with some form of reciprocity. from figure 2 , we observed that the best strategy-(po, po, eos)-is a triplet with higher success rates than the average. from a social science perspective, ending a request politely engenders a sense of liking and creates connections between the audience and requester, consistent with prior work showing that politeness is a social norm associated with ending a conversation @xcite . an example is shown in the first row in