# And That's A Fact: Distinguishing Factual and Emotional Argumentation in Online Dialogue

arXiv: https://arxiv.org/abs/1709.05295 · HTML: https://mlsanity.com/paper/1709.05295/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 Sep 2017.

## Built on by (most cited first, 5 of 5)

- [Computationally Identifying Funneling and Focusing Questions in Classroom Discourse](https://mlsanity.com/paper/2208.04715/) (2022)
- [Effectiveness of Counter-Speech against Abusive Content: A Multidimensional Annotation and Classification Study](https://mlsanity.com/paper/2506.11919/) (2025)
- [Efficient Multimodal Streaming Recommendation via Expandable Side Mixture-of-Experts](https://mlsanity.com/paper/2508.05993/) (2025)
- [FNDaaS: Content-agnostic Detection of Fake News sites](https://mlsanity.com/paper/2212.06492/) (2022)
- [Multi-Task Learning Improves Performance In Deep Argument Mining Models](https://mlsanity.com/paper/2307.01401/) (2023)

## Abstract (arXiv)

We investigate the characteristics of factual and emotional argumentation styles observed in online debates. Using an annotated set of "factual" and "feeling" debate forum posts, we extract patterns that are highly correlated with factual and emotional arguments, and then apply a bootstrapping methodology to find new patterns in a larger pool of unannotated forum posts. This process automatically produces a large set of patterns representing linguistic expressions that are highly correlated with factual and emotional language. Finally, we analyze the most discriminating patterns to better understand the defining characteristics of factual and emotional arguments.