Papers with Persuasion
FRAPPE: FRAming, Persuasion, and Propaganda Explorer (2024.eacl-demo)
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Ahmed Sajwani, Alaa El Setohy, Ali Mekky, Diana Turmakhan, Lara Hassan, Mohamed El Zeftawy, Omar El Herraoui, Osama Afzal, Qisheng Liao, Tarek Mahmoud
| Challenge: | FRAPPE is a linguistic analysis, persuasion, and propaganda-based news analysis system that analyzes articles for genre, framings, and persulasion techniques. |
| Approach: | They propose a FRAming, Persuasion, and Propaganda Explorer system that analyzes articles for genre, framings, and use of persuation techniques. |
| Outcome: | FRAPPE analyzes articles for genre, framings, and use of persuasion techniques . it also draws comparisons between persulasion and framping strategies adopted by a diverse pool of news outlets and countries across multiple languages for different topics . |
PEPDS: A Polite and Empathetic Persuasive Dialogue System for Charity Donation (2022.coling-1)
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| Challenge: | Empathy plays a crucial role in mediating the persuasive effects as it evokes cognitive and emotional processing conducive to persuasion. |
| Approach: | They propose to use a maximum likelihood estimate loss based model to design an efficient reward function consisting of five sub rewards viz. persuasion, emotion, Politeness-Strategy Consistency, Dialogue-Coherence and Non-repetitiveness. |
| Outcome: | The proposed system increases the rate of persuasive responses with emotion and politeness acknowledgement compared to the current state-of-the-art dialogue models while maintaining the linguistic quality. |
Empathetic Persuasion: Reinforcing Empathy and Persuasiveness in Dialogue Systems (2022.findings-naacl)
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| Challenge: | Existing models for persuasive dialogue lack emotion annotated data, so we use transformers to provide emotion based feedbacks to our RL agent. |
| Approach: | They propose to use a language model to generate empathetic persuasive dialogues . they annotate existing data with emotions and build transformers to provide feedbacks based on emotion. |
| Outcome: | The proposed model increases the rate of generating persuasive responses compared to state-of-the-art models while maintaining the language quality. |
Detecting Winning Arguments with Large Language Models and Persuasion Strategies (2026.findings-eacl)
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| 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. |
Examining the Ordering of Rhetorical Strategies in Persuasive Requests (2020.findings-emnlp)
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| 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. |
Enhancing Persuasive Dialogue Agents by Synthesizing Cross‐Disciplinary Communication Strategies (2025.emnlp-industry)
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Shinnosuke Nozue, Yuto Nakano, Yotaro Watanabe, Meguru Takasaki, Shoji Moriya, Reina Akama, Jun Suzuki
| Challenge: | Current approaches to developing persuasive dialogue agents rely on predefined persuasive strategies that fail to capture the complexity of real-world interactions. |
| Approach: | They propose a framework for designing persuasive dialogue agents that draws on proven strategies from social psychology, behavioral economics, and communication theory. |
| Outcome: | The proposed framework demonstrated significant improvement in the persuasion success rate and generalizability of the datasets. |
Argumentation Synthesis following Rhetorical Strategies (C18-1)
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| Challenge: | Existing argument mining studies focus on logical structure of arguments, identifying their units and relations, and the effects of logical and emotional arguments across audiences. |
| Approach: | They propose to use rhetorical strategies to synthesize argumentative texts with different strategies. |
| Outcome: | The proposed model shows that the experts agree significantly more on selection when following the same strategy. |
Zero-shot Persuasive Chatbots with LLM-Generated Strategies and Information Retrieval (2024.findings-emnlp)
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Kazuaki Furumai, Roberto Legaspi, Julio Romero, Yudai Yamazaki, Yasutaka Nishimura, Sina Semnani, Kazushi Ikeda, Weiyan Shi, Monica Lam
| Challenge: | Existing methods to improve persuasive chatbots use only a handful of predefined strategies. |
| Approach: | They propose a persuasive chatbot based on large language models that is factual and more persuasive by leveraging many more nuanced strategies. |
| Outcome: | The proposed chatbot is factual and more persuasive by leveraging many more nuanced strategies. |
Annotating the Annotators: Analysis, Insights and Modelling from an Annotation Campaign on Persuasion Techniques Detection (2025.findings-acl)
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Davide Bassi, Dimitar Iliyanov Dimitrov, Bernardo D’Auria, Firoj Alam, Maram Hasanain, Christian Moro, Luisa Orrù, Gian Piero Turchi, Preslav Nakov, Giovanni Da San Martino
| Challenge: | Existing annotation campaigns based on heuristic guidelines have not been thoroughly discussed. |
| Approach: | They propose a probabilistic model for optimizing intervention scheduling to reduce the cost of an expert oversight in annotation tasks. |
| Outcome: | The proposed model advocates for an expert oversight in annotation tasks and periodic quality audits to reduce costs. |