{
 "id": "oneonlee/cleansed_emocontext",
 "owner": "oneonlee",
 "name": "cleansed_emocontext",
 "downloads": 239,
 "likes": 2,
 "last_modified": "2024-03-10T10:24:36.000Z",
 "stated_licence": "mpl-2.0",
 "stated_from": "tag",
 "licence_name": null,
 "licence_link": null,
 "file_licence": null,
 "licence_files": [],
 "sources": [
  {
   "id": "emo",
   "licence": "unknown",
   "found": true,
   "evidence": "https://huggingface.co/datasets/SemEvalWorkshop/emo/blob/635e95332a716374a40a6f266db53513ea5a0a01/README.md"
  }
 ],
 "gated": false,
 "tasks": [
  "text-classification"
 ],
 "citation": "@inproceedings{chatterjee-etal-2019-semeval,\n    title={SemEval-2019 Task 3: EmoContext Contextual Emotion Detection in Text},\n    author={Ankush Chatterjee and Kedhar Nath Narahari and Meghana Joshi and Puneet Agrawal},\n    booktitle={Proceedings of the 13th International Workshop on Semantic Evaluation},\n    year={2019},\n    address={Minneapolis, Minnesota, USA},\n    publisher={Association for Computational Linguistics},\n    url={https://www.aclweb.org/anthology/S19-2005},\n    doi={10.18653/v1/S19-2005},\n    pages={39--48},\n    abstract={In this paper, we present the SemEval-2019 Task 3 - EmoContext: Contextual Emotion Detection in Text. Lack of facial expressions and voice modulations make detecting emotions in text a challenging problem. For instance, as humans, on reading ''Why don't you ever text me!'' we can either interpret it as a sad or angry emotion and the same ambiguity exists for machines. However, the context of dialogue can prove helpful in detection of the emotion. In this task, given a textual dialogue i.e. an utterance along with two previous turns of context, the goal was to infer the underlying emotion of the utterance by choosing from four emotion classes - Happy, Sad, Angry and Others. To facilitate the participation in this task, textual dialogues from user interaction with a conversational agent were taken and annotated for emotion classes after several data processing steps. A training data set of 30160 dialogues, and two evaluation data sets, Test1 ",
 "signal": "unclear",
 "reason": "The checks could not identify a recognised licence ID in the dataset's metadata.",
 "revision": "d96a144ecefc8600c28e711bbbb318f4fb8f5dbd",
 "stated_evidence": "https://huggingface.co/datasets/oneonlee/cleansed_emocontext/blob/d96a144ecefc8600c28e711bbbb318f4fb8f5dbd/README.md",
 "file_evidence": "https://huggingface.co/datasets/oneonlee/cleansed_emocontext/tree/d96a144ecefc8600c28e711bbbb318f4fb8f5dbd",
 "card_nc": false
}