Let’s Make Your Request More Persuasive: Modeling Persuasive Strategies via Semi-Supervised Neural Nets on Crowdfunding Platforms (N19-1)
Copied to clipboard
| Challenge: | Existing models can't quantify persuasiveness of requests or extract successful persuasive strategies. |
| Approach: | They propose a semi-supervised hierarchical neural network model to quantify persuasiveness and identify persuasive strategies in advocacy requests. |
| Outcome: | The proposed method outperforms baseline models and offers increased interpretability of persuasive speech. |
Similar Papers
Persuading across Diverse Domains: a Dataset and Persuasion Large Language Model (2024.acl-long)
Copied to clipboard
| Challenge: | Persuasive dialogue requires multi-turn following and planning abilities to achieve the goal of persuating users. |
| Approach: | They propose a general method to learn a persuasive model based on LLMs through intent-to-strategy reasoning, which summarizes the intent of user’s utterance and reasons next strategy to respond. |
| Outcome: | The proposed method outperforms baselines on automatic evaluation metric Win-Rate and human evaluation on two datasets. |
Measuring and Benchmarking Large Language Models’ Capabilities to Generate Persuasive Language (2025.naacl-long)
Copied to clipboard
| Challenge: | Recent studies have focused on specific domains or types of persuasion, but a general study has focused on how LLMs produce persuasive text. |
| Approach: | They construct a dataset to measure and benchmark the ability of Large Language Models (LLMs) to produce persuasive text. |
| Outcome: | The proposed model can be used to generate persuasive text across domains and domains. |
Revealing and Predicting Online Persuasion Strategy with Elementary Units (D19-1)
Copied to clipboard
| Challenge: | Existing studies have examined persuasive discourses with regard to dynamics or lexical features. |
| Approach: | They propose to annotate five types of EUs in a persuasive forum and propose a baseline neural model that identifies the EU boundary and type. |
| Outcome: | The proposed model reveals that EUs definitively characterize online persuasive strategies. |
Examining the Ordering of Rhetorical Strategies in Persuasive Requests (2020.findings-emnlp)
Copied to clipboard
| Challenge: | Numerous studies have been conducted to understand persuasiveness of text, from explorations of rhetoric in presidential campaigns to the impact of a communicator's likability on persuasiveness. |
| Approach: | They use a Variational Autoencoder model to disentangle content and rhetorical strategies in textual requests from a large-scale loan request corpus and visualize interplay between content and strategy through an attentional LSTM that predicts the success of textual request. |
| Outcome: | The proposed model disentangles content and rhetorical strategies in textual requests from a large-scale loan request corpus and visualizes interplay between content and strategy through attentional LSTM that predicts the success rate of textual request. |
Detecting Winning Arguments with Large Language Models and Persuasion Strategies (2026.findings-eacl)
Copied to clipboard
| Challenge: | Recent studies have focused on predicting winning arguments, i.e., those that effectively convince a reader to adopt a certain opinion. |
| Approach: | They propose to use large language models with a chain-of-thought framework to guide reasoning over six persuasion strategies to determine persuasiveness. |
| Outcome: | The proposed approach leverages large language models with a chain-of-thought framework that guides reasoning over six persuasion strategies. |
AutoPersuade: A Framework for Evaluating and Explaining Persuasive Arguments (2024.emnlp-main)
Copied to clipboard
| Challenge: | Existing tools for persuasion are well-equipped to identify which of a pre-existing set of messages is most persuasive, but they do not offer causal evidence on whether or how they have succeeded. |
| Approach: | They propose a framework for identifying topical components of persuasive arguments that are autopersuade. |
| Outcome: | The proposed framework validates the results through human studies and out-of-sample predictions. |
PVP: An Image Dataset for Personalized Visual Persuasion with Persuasion Strategies, Viewer Characteristics, and Persuasiveness Ratings (2025.acl-long)
Copied to clipboard
| Challenge: | Visual persuasion uses visual elements to influence cognition and behaviors . lack of comprehensive data sets connect persuasiveness of images with personal information . |
| Approach: | They propose to use a dataset to connect persuasiveness with personal information . they find psychological characteristics enhance the generation and evaluation of persuasive images . |
| Outcome: | The proposed dataset provides persuasiveness scores of images evaluated by human annotators along with demographic and psychological characteristics. |
ResPer: Computationally Modelling Resisting Strategies in Persuasive Conversations (2021.eacl-main)
Copied to clipboard
Ritam Dutt, Sayan Sinha, Rishabh Joshi, Surya Shekhar Chakraborty, Meredith Riggs, Xinru Yan, Haogang Bao, Carolyn Rose
| Challenge: | Existing research has failed to account for resisting strategies employed to foil persuasion attempts. |
| Approach: | They propose a framework for identifying resisting strategies in persuasive conversations . they instantiate a dataset comprising persuasion and negotiation conversations based on a hierarchical sequence-labelling neural architecture . |
| Outcome: | The proposed framework is based on two persuasive conversation datasets and leverages a hierarchical sequence-labelling neural architecture to infer resisting strategies automatically. |
Understanding User Resistance Strategies in Persuasive Conversations (2020.findings-emnlp)
Copied to clipboard
| Challenge: | Persuasive dialog systems have various usages, such as donation persuation and physical exercise persulasion. |
| Approach: | They adopt a preliminary framework on persuasion resistance in psychology and build a fine-grained resistance strategy annotation scheme to analyze the persuitee's resistance strategies. |
| Outcome: | The proposed system can understand and address user resistance strategies appropriately. |
Exploring the Usability of Persuasion Techniques for Downstream Misinformation-related Classification Tasks (2024.lrec-main)
Copied to clipboard
| Challenge: | systematically explore the predictive power of features derived from Persuasion Techniques detected in texts for different tasks of interest for media analysis. |
| Approach: | They propose a set of meaningful features aimed at capturing persuasiveness of a text . they also assess the discriminatory power of these features in different text classification tasks . |
| Outcome: | The proposed features can be applied to detecting mis/disinformation, fake news, propaganda, partisan news and conspiracy theories. |