Datasets:

silver
/

mmchat

	---
	annotations_creators:
	- no-annotation
	language_creators:
	- found
	language:
	- zh
	license:
	- other
	multilinguality:
	- monolingual
	paperswithcode_id: mmchat-multi-modal-chat-dataset-on-social
	pretty_name: "MMChat: Multi-Modal Chat Dataset on Social Media"
	size_categories:
	- 10M<n<100M
	source_datasets:
	- original
	task_categories:
	- conversational
	task_ids:
	- dialogue-generation
	---

	# Dataset Card for MMChat

	## Table of Contents
	- [Dataset Card for MMChat](#dataset-card-for-mmchat)
	- [Table of Contents](#table-of-contents)
	- [Dataset Description](#dataset-description)
	- [Dataset Summary](#dataset-summary)
	- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
	- [Languages](#languages)
	- [Dataset Structure](#dataset-structure)
	- [Data Instances](#data-instances)
	- [Data Fields](#data-fields)
	- [Data Splits](#data-splits)
	- [Dataset Creation](#dataset-creation)
	- [Curation Rationale](#curation-rationale)
	- [Source Data](#source-data)
	- [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
	- [Who are the source language producers?](#who-are-the-source-language-producers)
	- [Annotations](#annotations)
	- [Annotation process](#annotation-process)
	- [Who are the annotators?](#who-are-the-annotators)
	- [Personal and Sensitive Information](#personal-and-sensitive-information)
	- [Considerations for Using the Data](#considerations-for-using-the-data)
	- [Social Impact of Dataset](#social-impact-of-dataset)
	- [Discussion of Biases](#discussion-of-biases)
	- [Other Known Limitations](#other-known-limitations)
	- [Additional Information](#additional-information)
	- [Dataset Curators](#dataset-curators)
	- [Licensing Information](#licensing-information)
	- [Citation Information](#citation-information)
	- [Contributions](#contributions)

	## Dataset Description

	- Homepage: https://www.zhengyinhe.com/datasets/
	- Repository: https://github.com/silverriver/MMChat
	- Paper: https://arxiv.org/abs/2108.07154

	### Dataset Summary

	MMChat is a large-scale dialogue dataset that contains image-grounded dialogues in Chinese. Each dialogue in MMChat is associated with one or more images (maximum 9 images per dialogue). We design various strategies to ensure the quality of the dialogues in MMChat.

	MMChat comes with 4 different versions:

	- `mmchat`: The MMChat dataset used in our paper.
	- `mmchat_hf`: Contains human annotation on 100K sessions of dialogues.
	- `mmchat_raw`: Raw dialogues used to construct MMChat.
	`mmchat_lccc_filtered`: Raw dialogues filtered using the LCCC dataset.

	If you what to use high quality multi-modal dialogues that are closed related to the given images, I suggest you to use the `mmchat_hf` version.
	If you only care about the quality of dialogue texts, I suggest you to use the `mmchat_lccc_filtered` version.

	### Supported Tasks and Leaderboards

	- dialogue-generation: The dataset can be used to train a model for generating dialogue responses.
	- response-retrieval: The dataset can be used to train a reranker model that can be used to implement a retrieval-based dialogue model.

	### Languages

	MMChat is in Chinese

	MMChat中的对话是中文的

	## Dataset Structure

	### Data Instances

	Several versions of MMChat are available. For `mmchat`, `mmchat_raw`, `mmchat_lccc_filtered`, the following instance applies:

	```json
	{
	"dialog": ["你只拍出了你十分之一的美", "你的头像竟然换了，奥"],
	"weibo_content": "分享图片",
	"imgs": ["https://wx4.sinaimg.cn/mw2048/d716a6e2ly1fmug2w2l9qj21o02yox6p.jpg"]
	}
	```

	For `mmchat_hf`, the following instance applies:

	```json
	{
	"dialog": ["白百合", "啊？", "有点像", "还好吧哈哈哈牙像", "有男盆友没呢", "还没", "和你说话呢。没回我"],
	"weibo_content": "补一张昨天礼仪的照片",
	"imgs": ["https://ww2.sinaimg.cn/mw2048/005Co9wdjw1eyoz7ib9n5j307w0bu3z5.jpg"],
	"labels": {
	"image_qualified": true,
	"dialog_qualified": true,
	"dialog_image_related": true
	}
	}
	```

	### Data Fields

	- `dialog` (list of strings): List of utterances consisting of a dialogue.
	- `weibo_content` (string): Weibo content of the dialogue.
	- `imgs` (list of strings): List of URLs of images.
	- `labels` (dict): Human-annotated labels of the dialogue.
	- `image_qualified` (bool): Whether the image is of high quality.
	- `dialog_qualified` (bool): Whether the dialogue is of high quality.
	- `dialog_image_related` (bool): Whether the dialogue is related to the image.

	### Data Splits

	For `mmchat`, we provide the following splits:

	\|train\|valid\|test\|
	\|---:\|---:\|---:\|
	\|115,842 \| 4,000 \| 1,000 \|

	For other versions, we do not provide the offical split.
	More stastics are listed here:

	\| `mmchat` \| Count \|
	\|--------------------------------------\|--------:\|
	\| Sessions \| 120.84 K \|
	\| Sessions with more than 4 utterances \| 17.32 K \|
	\| Utterances \| 314.13 K \|
	\| Images \| 198.82 K \|
	\| Avg. utterance per session \| 2.599 \|
	\| Avg. image per session \| 2.791 \|
	\| Avg. character per utterance \| 8.521 \|

	\| `mmchat_hf` \| Count \|
	\|--------------------------------------\|--------:\|
	\| Sessions \| 19.90 K \|
	\| Sessions with more than 4 utterances \| 8.91 K \|
	\| Totally annotated sessions \| 100.01 K \|
	\| Utterances \| 81.06 K \|
	\| Images \| 52.66K \|
	\| Avg. utterance per session \| 4.07 \|
	\| Avg. image per session \| 2.70 \|
	\| Avg. character per utterance \| 11.93 \|

	\| `mmchat_raw` \| Count \|
	\|--------------------------------------\|---------:\|
	\| Sessions \| 4.257 M \|
	\| Sessions with more than 4 utterances \| 2.304 M \|
	\| Utterances \| 18.590 M \|
	\| Images \| 4.874 M \|
	\| Avg. utterance per session \| 4.367 \|
	\| Avg. image per session \| 1.670 \|
	\| Avg. character per utterance \| 14.104 \|

	\| `mmchat_lccc_filtered` \| Count \|
	\|--------------------------------------\|--------:\|
	\| Sessions \| 492.6 K \|
	\| Sessions with more than 4 utterances \| 208.8 K \|
	\| Utterances \| 1.986 M \|
	\| Images \| 1.066 M \|
	\| Avg. utterance per session \| 4.031 \|
	\| Avg. image per session \| 2.514 \|
	\| Avg. character per utterance \| 11.336 \|

	## Dataset Creation

	### Curation Rationale

	[Needs More Information]

	### Source Data

	#### Initial Data Collection and Normalization

	[Needs More Information]

	#### Who are the source language producers?

	[Needs More Information]

	### Annotations

	#### Annotation process

	[Needs More Information]

	#### Who are the annotators?

	[Needs More Information]

	### Personal and Sensitive Information

	[Needs More Information]

	## Considerations for Using the Data

	### Social Impact of Dataset

	[Needs More Information]

	### Discussion of Biases

	[Needs More Information]

	### Other Known Limitations

	[Needs More Information]

	## Additional Information

	### Dataset Curators

	[Needs More Information]

	### Licensing Information

	other-weibo

	This dataset is collected from Weibo.
	You can refer to the [detailed policy](https://weibo.com/signup/v5/privacy) required to use this dataset.
	Please restrict the usage of this dataset to non-commerical purposes.

	### Citation Information

	```
	@inproceedings{zheng2022MMChat,
	author = {Zheng, Yinhe and Chen, Guanyi and Liu, Xin and Sun, Jian},
	title = {MMChat: Multi-Modal Chat Dataset on Social Media},
	booktitle = {Proceedings of The 13th Language Resources and Evaluation Conference},
	year = {2022},
	publisher = {European Language Resources Association},
	}

	@inproceedings{wang2020chinese,
	title={A Large-Scale Chinese Short-Text Conversation Dataset},
	author={Wang, Yida and Ke, Pei and Zheng, Yinhe and Huang, Kaili and Jiang, Yong and Zhu, Xiaoyan and Huang, Minlie},
	booktitle={NLPCC},
	year={2020},
	url={https://arxiv.org/abs/2008.03946}
	}
	```

	### Contributions

	Thanks to [Yinhe Zheng](https://github.com/silverriver) for adding this dataset.