README.md

metadata

annotations_creators:
  - crowdsourced
language_creators:
  - crowdsourced
languages:
  - en
licenses:
  - unknown
multilinguality:
  - monolingual
size_categories:
  - 10K<n<100K
source_datasets:
  - original
task_categories:
  - text-classification
task_ids:
  - sentiment-classification
paperswithcode_id: reactiongif

ReactionGIF

From https://github.com/bshmueli/ReactionGIF

---

Excerpt from original repo readme

ReactionGIF is a unique, first-of-its-kind dataset of 30K sarcastic tweets and their GIF reactions.

To find out more about ReactionGIF, check out our ACL 2021 paper:

• Shmueli, Ray and Ku, Happy Dance, Slow Clap: Using Reaction GIFs to Predict Induced Affect on Twitter

Citation

If you use our dataset, kindly cite the paper using the following BibTex entry:

@misc{shmueli2021happy,
      title={Happy Dance, Slow Clap: Using Reaction {GIFs} to Predict Induced Affect on {Twitter}}, 
      author={Boaz Shmueli and Soumya Ray and Lun-Wei Ku},
      year={2021},
      eprint={2105.09967},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}