# Effects of Persuasive Dialogues: Testing Bot Identities and Inquiry Strategies

arXiv: https://arxiv.org/abs/2001.04564 · HTML: https://mlsanity.com/paper/2001.04564/

## Key facts

- Cited by 29 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Jan 2020.

## Built on by (most cited first, 29 of 29)

- [Leveraging Large Language Models to Power Chatbots for Collecting User Self-Reported Data](https://mlsanity.com/paper/2301.05843/) (2023)
- [Controllable Mixed-Initiative Dialogue Generation through Prompting](https://mlsanity.com/paper/2305.04147/) (2023)
- [Human Decision-making is Susceptible to AI-driven Manipulation](https://mlsanity.com/paper/2502.07663/) (2025)
- [PersuasiveToM: A Benchmark for Evaluating Machine Theory of Mind in Persuasive Dialogues](https://mlsanity.com/paper/2502.21017/) (2025)
- [Multi-Agents are Social Groups: Investigating Social Influence of Multiple Agents in Human-Agent Interactions](https://mlsanity.com/paper/2411.04578/) (2024)
- [Contextualized Counterspeech: Strategies for Adaptation, Personalization, and Evaluation](https://mlsanity.com/paper/2412.07338/) (2024)
- [Zero-shot Persuasive Chatbots with LLM-Generated Strategies and Information Retrieval](https://mlsanity.com/paper/2407.03585/) (2024)
- [Labeling Messages as AI-Generated Does Not Reduce Their Persuasive Effects](https://mlsanity.com/paper/2504.09865/) (2025)
- [Must Read: A Comprehensive Survey of Computational Persuasion](https://mlsanity.com/paper/2505.07775/) (2025)
- [The Illusion of Empathy: How AI Chatbots Shape Conversation Perception](https://mlsanity.com/paper/2411.12877/) (2024)
- [ToMAP: Training Opponent-Aware LLM Persuaders with Theory of Mind](https://mlsanity.com/paper/2505.22961/) (2025)
- [An LLM Feature-based Framework for Dialogue Constructiveness Assessment](https://mlsanity.com/paper/2406.14760/) (2024)
- [Opening up Minds with Argumentative Dialogues](https://mlsanity.com/paper/2301.06400/) (2023)
- [Large Language Models as Misleading Assistants in Conversation](https://mlsanity.com/paper/2407.11789/) (2024)
- [The Future of Cognitive Strategy-enhanced Persuasive Dialogue Agents: New Perspectives and Trends](https://mlsanity.com/paper/2402.04631/) (2024)
- [On LLM Wizards: Identifying Large Language Models' Behaviors for Wizard of Oz Experiments](https://mlsanity.com/paper/2407.08067/) (2024)
- [This Is Your Doge, If It Please You: Exploring Deception and Robustness in Mixture of LLMs](https://mlsanity.com/paper/2503.05856/) (2025)
- [Counterfactual Reasoning Using Predicted Latent Personality Dimensions for Optimizing Persuasion Outcome](https://mlsanity.com/paper/2404.13792/) (2024)
- [Enhancing Dialogue Generation in Werewolf Game Through Situation Analysis and Persuasion Strategies](https://mlsanity.com/paper/2408.16586/) (2024)
- [Causal Discovery and Counterfactual Reasoning to Optimize Persuasive Dialogue Policies](https://mlsanity.com/paper/2503.16544/) (2025)
- [The Bots of Persuasion: Examining How Conversational Agents' Linguistic Expressions of Personality Affect User Perceptions and Decisions](https://mlsanity.com/paper/2602.17185/) (2026)
- [Personalized to Persuade: The Effects of Contextualization and Warmth on Trust and Reliance in Conversational AI](https://mlsanity.com/paper/2605.31275/) (2026)
- [Wild Narratives: Exploring the Effects of Animal Chatbots on Empathy and Positive Attitudes toward Animals](https://mlsanity.com/paper/2411.06060/) (2024)
- [Polite But Boring? Trade-offs Between Engagement and Psychological Reactance to Chatbot Feedback Styles](https://mlsanity.com/paper/2601.20683/) (2026)
- [Multi-Agent Systems Shape Social Norms for Prosocial Behavior Change](https://mlsanity.com/paper/2602.07433/) (2026)
- [Enhancing Persuasive Dialogue Agents by Synthesizing Cross-Disciplinary Communication Strategies](https://mlsanity.com/paper/2602.22696/) (2026)
- [More Isn't Always Better: Balancing Decision Accuracy and Conformity Pressures in Multi-AI Advice](https://mlsanity.com/paper/2603.22152/) (2026)
- [Will you donate money to a chatbot? The effect of chatbot anthropomorphic features and persuasion strategies on willingness to donate](https://mlsanity.com/paper/2412.19976/) (2024)
- [Psi-Bench: Evaluating Persona-Sensitive Influencing in Persuasive Dialogues](https://mlsanity.com/paper/2606.02754/) (2026)

## Abstract (arXiv)

Intelligent conversational agents, or chatbots, can take on various identities and are increasingly engaging in more human-centered conversations with persuasive goals. However, little is known about how identities and inquiry strategies influence the conversation's effectiveness. We conducted an online study involving 790 participants to be persuaded by a chatbot for charity donation. We designed a two by four factorial experiment (two chatbot identities and four inquiry strategies) where participants were randomly assigned to different conditions. Findings showed that the perceived identity of the chatbot had significant effects on the persuasion outcome (i.e., donation) and interpersonal perceptions (i.e., competence, confidence, warmth, and sincerity). Further, we identified interaction effects among perceived identities and inquiry strategies. We discuss the findings for theoretical and practical implications for developing ethical and effective persuasive chatbots. Our published data, codes, and analyses serve as the first step towards building competent ethical persuasive chatbots.