Dataset for COLING 2022 "Towards Exploiting Sticker for Multimodal Sentiment Analysis in Social Media: A New Dataset and Baseline"
Currently, we only offer downloads with labeled data. The unlabeled data will be released soon.
- Sign the copyright announcement with your name and organization and mail to logosg@foxmail.com with the copyright announcement attachment.
- Then complete the form online(https://forms.gle/UaU7DG25DmZBSjBH6), and we will provide access rights when approved.
The original copyright of all the conversations belongs to the source owner. The copyright of the annotations belongs to our group, and they are free to the public. The dataset is only for research purposes. Without permission, it may not be used for any commercial purposes or distributed to others.
stickers_labeled: stores all the stickers in the labeled dataset.
CSMSA_labeled: stores the labeled dataset.
| Json Key Name | Description |
|---|---|
| text | input text |
| image | image name in stickers |
| multimodal_label | the sentiment of the text and image. 0 indicates Neutral, 1 indicates Postive, 2 indicates Negative |
| text_label | the sentiment of the text |
| image_label | the sentiment of the sticker |
| img_helps_text | 0 indicates no, 1 indicates yes |
| sticker_group | the series number of the sticker |
@inproceedings{ge-etal-2022-towards,
title = "Towards Exploiting Sticker for Multimodal Sentiment Analysis in Social Media: A New Dataset and Baseline",
author = "Ge, Feng and Li, Weizhao and Ren, Haopeng and Cai, Yi",
booktitle = "Proceedings of the 29th International Conference on Computational Linguistics",
month = oct,
year = "2022",
address = "Gyeongju, Republic of Korea",
publisher = "International Committee on Computational Linguistics",
url = "https://aclanthology.org/2022.coling-1.591",
pages = "6795--6804",
}