# Dealing with Controversy: An Emotion and Coping Strategy Corpus Based on Role Playing

arXiv: https://arxiv.org/abs/2409.19025 · HTML: https://mlsanity.com/paper/2409.19025/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 11 of its 50 references that are in the map.
- First posted on arXiv 26 Sep 2024.

## Builds on (most cited first, 11 of 11)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter](https://mlsanity.com/paper/1910.01108/) (2019)
- [GoEmotions: A Dataset of Fine-Grained Emotions](https://mlsanity.com/paper/2005.00547/) (2020)
- [SpanEmo: Casting Multi-label Emotion Classification as Span-prediction](https://mlsanity.com/paper/2101.10038/) (2021)
- [Inducing Positive Perspectives with Text Reframing](https://mlsanity.com/paper/2204.02952/) (2022)
- [Dimensional Emotion Detection from Categorical Emotion](https://mlsanity.com/paper/1911.02499/) (2019)
- [Emotion Dynamics in Movie Dialogues](https://mlsanity.com/paper/2103.01345/) (2021)
- [Empathetic Dialogue Generation via Sensitive Emotion Recognition and Sensible Knowledge Selection](https://mlsanity.com/paper/2210.11715/) (2022)
- [Emotion Recognition based on Psychological Components in Guided Narratives for Emotion Regulation](https://mlsanity.com/paper/2305.10446/) (2023)
- [Where are We in Event-centric Emotion Analysis? Bridging Emotion Role Labeling and Appraisal-based Approaches](https://mlsanity.com/paper/2309.02092/) (2023)

## Built on by (most cited first, 4 of 4)

- [Trust Me, I Can Convince You: The Contextualized Argument Appraisal Framework](https://mlsanity.com/paper/2509.17844/) (2025)
- [Donate or Create? Comparing Data Collection Strategies for Emotion-labeled Multimodal Social Media Posts](https://mlsanity.com/paper/2505.24427/) (2025)
- [Categorical Emotions or Appraisals - Which Emotion Model Explains Argument Convincingness Better?](https://mlsanity.com/paper/2511.07162/) (2025)
- [Linguistic Distancing on Social Media: Indicators of Emotion Regulation Across Age Groups](https://mlsanity.com/paper/2606.30957/) (2026)

## Abstract (arXiv)

There is a mismatch between psychological and computational studies on emotions. Psychological research aims at explaining and documenting internal mechanisms of these phenomena, while computational work often simplifies them into labels. Many emotion fundamentals remain under-explored in natural language processing, particularly how emotions develop and how people cope with them. To help reduce this gap, we follow theories on coping, and treat emotions as strategies to cope with salient situations (i.e., how people deal with emotion-eliciting events). This approach allows us to investigate the link between emotions and behavior, which also emerges in language. We introduce the task of coping identification, together with a corpus to do so, constructed via role-playing. We find that coping strategies realize in text even though they are challenging to recognize, both for humans and automatic systems trained and prompted on the same task. We thus open up a promising research direction to enhance the capability of models to better capture emotion mechanisms from text.