# Persua: A Visual Interactive System to Enhance the Persuasiveness of Arguments in Online Discussion

arXiv: https://arxiv.org/abs/2204.07741 · HTML: https://mlsanity.com/paper/2204.07741/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- Builds on 12 of its 81 references that are in the map.
- First posted on arXiv 16 Apr 2022.

## Builds on (most cited first, 12 of 12)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Deep contextualized word representations](https://mlsanity.com/paper/1802.05365/) (2018)
- [Persuasion for Good: Towards a Personalized Persuasive Dialogue System for Social Good](https://mlsanity.com/paper/1906.06725/) (2019)
- [Winning Arguments: Interaction Dynamics and Persuasion Strategies in Good-faith Online Discussions](https://mlsanity.com/paper/1602.01103/) (2016)
- [Classification and Clustering of Arguments with Contextualized Word Embeddings](https://mlsanity.com/paper/1906.09821/) (2019)
- [Exploring the Role of Prior Beliefs for Argument Persuasion](https://mlsanity.com/paper/1906.11301/) (2019)
- [Are You Convinced? Choosing the More Convincing Evidence with a Siamese Network](https://mlsanity.com/paper/1907.08971/) (2019)
- [EmoCo: Visual Analysis of Emotion Coherence in Presentation Videos](https://mlsanity.com/paper/1907.12918/) (2019)
- [Effective Interfaces for Student-Driven Revision Sessions for Argumentative Writing](https://mlsanity.com/paper/2107.07018/) (2021)
- [VoiceCoach: Interactive Evidence-based Training for Voice Modulation Skills in Public Speaking](https://mlsanity.com/paper/2001.07876/) (2020)
- [Exploring Discourse Structures for Argument Impact Classification](https://mlsanity.com/paper/2106.00976/) (2021)
- [ArguLens: Anatomy of Community Opinions On Usability Issues Using Argumentation Models](https://mlsanity.com/paper/2001.06067/) (2020)

## Built on by (most cited first, 7 of 7)

- [VISAR: A Human-AI Argumentative Writing Assistant with Visual Programming and Rapid Draft Prototyping](https://mlsanity.com/paper/2304.07810/) (2023)
- [XNLI: Explaining and Diagnosing NLI-based Visual Data Analysis](https://mlsanity.com/paper/2301.10385/) (2023)
- [Storyfier: Exploring Vocabulary Learning Support with Text Generation Models](https://mlsanity.com/paper/2308.03864/) (2023)
- [GestureLens: Visual Analysis of Gestures in Presentation Videos](https://mlsanity.com/paper/2204.08894/) (2022)
- [Iffy-Or-Not: Extending the Web to Support the Critical Evaluation of Fallacious Texts](https://mlsanity.com/paper/2503.14412/) (2025)
- [Teach Me How to Improve My Argumentation Skills: A Survey on Feedback in Argumentation](https://mlsanity.com/paper/2307.15341/) (2023)
- [A Model of Multi-turn Human Persuadability Using Probabilistic Belief Tracing](https://mlsanity.com/paper/2606.05330/) (2026)

## Abstract (arXiv)

Persuading people to change their opinions is a common practice in online discussion forums on topics ranging from political campaigns to relationship consultation. Enhancing people's ability to write persuasive arguments could not only practice their critical thinking and reasoning but also contribute to the effectiveness and civility in online communication. It is, however, not an easy task in online discussion settings where written words are the primary communication channel. In this paper, we derived four design goals for a tool that helps users improve the persuasiveness of arguments in online discussions through a survey with 123 online forum users and interviews with five debating experts. To satisfy these design goals, we analyzed and built a labeled dataset of fine-grained persuasive strategies (i.e., logos, pathos, ethos, and evidence) in 164 arguments with high ratings on persuasiveness from ChangeMyView, a popular online discussion forum. We then designed an interactive visual system, Persua, which provides example-based guidance on persuasive strategies to enhance the persuasiveness of arguments. In particular, the system constructs portfolios of arguments based on different persuasive strategies applied to a given discussion topic. It then presents concrete examples based on the difference between the portfolios of user input and high-quality arguments in the dataset. A between-subjects study shows suggestive evidence that Persua encourages users to submit more times for feedback and helps users improve more on the persuasiveness of their arguments than a baseline system. Finally, a set of design considerations was summarized to guide future intelligent systems that improve the persuasiveness in text.