Persuasion for Good: Towards a Personalized Persuasive Dialogue System for Social Good
Open accessAbstract
Developing intelligent persuasive conversational agents to change people's opinions and actions for social good is the frontier in advancing the ethical development of automated dialogue systems.To do so, the first step is to understand the intricate organization of strategic disclosures and appeals employed in human persuasion conversations.We designed an online persuasion task where one participant was asked to persuade the other to donate to a specific charity.We collected a large dataset with 1,017 dialogues and annotated emerging persuasion strategies from a subset.Based on the annotation, we built a baseline classifier with context information and sentence-level features to predict the 10 persuasion strategies used in the corpus.Furthermore, to develop an understanding of personalized persuasion processes, we analyzed the relationships between individuals' demographic and psychological backgrounds including personality, morality, value systems, and their willingness for donation.Then, we analyzed which types of persuasion strategies led to a greater amount of donation depending on the individuals' personal backgrounds.This work lays the ground for developing a personalized persuasive dialogue system. 1
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Past literature has examined useful characteristics for personalized influences, such as using different persuasive strategies to appeal to different personality traits or setting personalized change goals based on behavior habits.
“Past literature has examined a number of useful characteristics for personalized influences, such as using different persuasive strategies to appeal to different personality traits [53,68] or setting personalized change goals based on behavior habits [42].”
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- Authors
- Wang, X., Shi, W., Kim, R., Oh, Y., Yang, S., Zhang, J., & Yu, Z.
- Affiliations
- Zhejiang University (CN)
- University of California, Davis (US)
- University of Pennsylvania (US)
- Venue
- Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
- Published
- 2019
- Pages
- 5635-5649
- ISSN
- 0736-587X (ISSN-L)
- OpenAlex
- W2952607215
- Cited by
- 222
- References
- 42
- Citations by year
- 2026: 15 · 2025: 22 · 2024: 31 · 2023: 47 · 2022: 41 · 2021: 40 · 2020: 24 · 2019: 2
- FWCI
- 10.24
- Type
- conference paper
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by
- Locations
- Proceedings of the conference - Association for Computational Linguistics. Meeting (publishedVersion, cc-by)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Speech and dialogue systems
- Social Sciences › Sociology and Political Science › Psychology of Social Influence
- Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
- Keywords
- persuasion techniques, personalized persuasion, social good, personality, morality, values, willingness to donate, chatbots, ethical AI
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