# Reactive Supervision: A New Method for Collecting Sarcasm Data

arXiv: https://arxiv.org/abs/2009.13080 · HTML: https://mlsanity.com/paper/2009.13080/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Sep 2020.

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

- [A Survey in Automatic Irony Processing: Linguistic, Cognitive, and Multi-X Perspectives](https://mlsanity.com/paper/2209.04712/) (2022)
- [Perceived and Intended Sarcasm Detection with Graph Attention Networks](https://mlsanity.com/paper/2110.04001/) (2021)
- [Computational Sarcasm Analysis on Social Media: A Systematic Review](https://mlsanity.com/paper/2209.06170/) (2022)
- ["When Words Fail, Emojis Prevail": Generating Sarcastic Utterances with Emoji Using Valence Reversal and Semantic Incongruity](https://mlsanity.com/paper/2305.04105/) (2023)

## Abstract (arXiv)

Sarcasm detection is an important task in affective computing, requiring large amounts of labeled data. We introduce reactive supervision, a novel data collection method that utilizes the dynamics of online conversations to overcome the limitations of existing data collection techniques. We use the new method to create and release a first-of-its-kind large dataset of tweets with sarcasm perspective labels and new contextual features. The dataset is expected to advance sarcasm detection research. Our method can be adapted to other affective computing domains, thus opening up new research opportunities.